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[FCO] M.L.Engineer.Nano v2.0.0
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文件列表
Part 02-Module 04-Lesson 02_Deep Q-Learning/07. Experience Replay-wX_-SZG-YMQ.mp4
50.7 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/07. M2L3 07 V2-ZBLLGIN1EfU.mp4
45.7 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.mp4
42.7 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/10. DQN Improvements-Zfdbp93A2GU.mp4
41.3 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/03. MC Prediction State Values-0q2wSWyuBj8.mp4
35.0 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/01. Deep Reinforcement Learning-GPjK124RU5g.mp4
34.8 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.mp4
34.2 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/02. Meet Chris-0ccflD9x5WU.mp4
34.1 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/02. M2L3 02 V2-ToS8vXGdODE.mp4
34.1 MB
Part 01-Module 13-Lesson 01_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4
34.0 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.mp4
33.2 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/14. Policy Improvement-4_adUEK0IHg.mp4
31.9 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/03. TD Prediction TD(0)-CsD6b0csU7o.mp4
31.6 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/11. Linear Function Approximation-OJ5wrB7o-pI.mp4
30.1 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/05. An Iterative Method-AX-hG3KvwzY.mp4
28.9 MB
Part 01-Module 01-Lesson 01_Welcome to Machine Learning/01. 01 Boas-vindas ao programa IntroduçãoMLND V3-A8AnsR6e75I.mp4
28.3 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/13. SVM 11 Polynomial Kernel 3 V1-XmbK8OjbX5U.mp4
28.1 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.mp4
27.6 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/06. Deep Q Network-GgtR_d1OB-M.mp4
26.9 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/14. Interview with Art - Part 3-M6PKr3S1rPg.mp4
26.3 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.mp4
24.5 MB
Part 01-Module 11-Lesson 01_Clustering/13. Sklearn-3zHUAXcoZ7c.mp4
24.4 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.mp4
24.3 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.mp4
23.6 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/06. MC Prediction Action Values-08tLtbh0xLs.mp4
23.1 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/13. MC Control Policy Improvement-2RKH-BInX7s.mp4
23.1 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/05. Interview with Art - Part 1-ClLYamtaO-Q.mp4
22.8 MB
Part 01-Module 10-Lesson 03_Decision Trees/01. MLND SL DT 00 Intro V2-l34ijtQhVNk.mp4
22.7 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/03. Discrete vs. Continuous Spaces-uHstLeRzaE8.mp4
22.4 MB
Part 01-Module 10-Lesson 04_Naive Bayes/04. SL NB 03 Guess The Person Now V1 V2-pQgO1KF90yU.mp4
22.1 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/04. M2L3 04 V1-QicxmyE5vTo.mp4
22.0 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/08. Fixed Q Targets-SWpyiEezfp4.mp4
22.0 MB
Part 01-Module 13-Lesson 01_PCA/28. PCA in sklearn-SBYdqlLgbGk.mp4
21.9 MB
Part 01-Module 13-Lesson 01_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.mp4
21.8 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.mp4
21.7 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/03. Elevator Pitch-S-nAHPrkQrQ.mp4
21.6 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/02. Policies-hc3LrvaC13U.mp4
21.2 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/10. Function Approximation-UTGWVY6jEdg.mp4
21.1 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/10. MC Control Incremental Mean-E2RITH-2NUE.mp4
21.0 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.mp4
20.9 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.mp4
20.7 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/03. M2L3 03 V2-TePX-0Bs23E.mp4
19.8 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/07. SVM 06 Margin Error V2-dSac8Gfgbok.mp4
19.7 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/14. SVM 12 RBF Kernel 1 V3-xdkIulxXWfQ.mp4
19.5 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/17. CNNs For Image Classification-l9vg_1YUlzg.mp4
19.0 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.mp4
19.0 MB
Part 01-Module 13-Lesson 01_PCA/17. Composite Features-spVqFnSvlIU.mp4
19.0 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.mp4
18.6 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/02. Aplicações de CNNs-HrYNL_1SV2Y.mp4
18.6 MB
Part 01-Module 13-Lesson 01_PCA/29. When to Use PCA-hJZHcmJBk1o.mp4
18.4 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/09. Deep Q-Learning Algorithm-MqTXoCxQ_eY.mp4
18.3 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/01. Why Network-exjEm9Paszk.mp4
18.2 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/05. Q-Learning-AI5gLgYMSq8.mp4
18.2 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/11. Camadas convolucionais-RnM1D-XI--8.mp4
17.9 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/04. Temporal Difference Learning-lpmDi0QeUm8.mp4
17.8 MB
Part 02-Module 04-Lesson 04_Actor-Critic Methods/07. Summary-hvYQ_3LgCYs.mp4
17.7 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/05. M2L3 05 V1-eZxxNNIZuwA.mp4
17.5 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/10. TD Control Sarsamax-4DxoYuR7aZ4.mp4
17.3 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/01. Introduction-bYeteZQrUcE.mp4
16.8 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/23. Value Iteration-XNeQn8N36y8.mp4
16.4 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.mp4
16.2 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/04. Neural Networks-Mqogpnp1lrU.mp4
15.6 MB
Part 01-Module 12-Lesson 01_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.mp4
15.6 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.mp4
15.5 MB
Part 01-Module 10-Lesson 04_Naive Bayes/07. SL NB 06 S False Positives V1 V3-Bg6_Tvcv81A.mp4
15.1 MB
Part 01-Module 05-Lesson 01_Training and Testing Models/09. Testing-gmxGRJSKEb0.mp4
15.0 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/11. Discounted Return-opXGNPwwn7g.mp4
15.0 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/20. Truncated Policy Iteration-a-RvCxlPMho.mp4
14.8 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/25. Transfer Learning-LHG5FltaR6I.mp4
14.0 MB
Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.mp4
13.9 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/21. K-means Clustering-pv_i08zjpQw.mp4
13.8 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4
13.8 MB
Part 01-Module 10-Lesson 03_Decision Trees/14. Maximizing Information Gain-3FgJOpKfdY8.mp4
13.8 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/05. SVM 04 Perceptron Algorithm V1-IIlQHBOrD6Q.mp4
13.6 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/26. Transfer Learning in Keras-HsIAznMM1LA.mp4
13.6 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/04. Decision Trees Answer-h8zH47iFhCo.mp4
13.3 MB
Part 01-Module 11-Lesson 01_Clustering/02. Unsupervised Learning-Mx9f99bRB3Q.mp4
13.3 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/02. Neural Nets as Value Functions-cBi7vLrk8QQ.mp4
13.3 MB
Part 01-Module 13-Lesson 01_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.mp4
13.2 MB
Part 01-Module 10-Lesson 03_Decision Trees/07. Entropy-piLpj1V1HEk.mp4
13.2 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/06. SVM 05 Classification Error V1-nWGVAGXwvGE.mp4
13.2 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/05. Discretization-j2eZyUpy--E.mp4
13.2 MB
Part 01-Module 13-Lesson 01_PCA/16. Compression While Preserving Information-NjuenhkC-44.mp4
13.1 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/18. MC Control Constant-alpha-QFV1nI9Zpoo.mp4
13.1 MB
Part 01-Module 10-Lesson 03_Decision Trees/09. MLND SL DT 08 Entropy Formula 2 MAIN V2-6GHg70hrSJw.mp4
12.9 MB
Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.mp4
12.7 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/09. Local Connectivity-z9wiDg0w-Dc.mp4
12.6 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.mp4
12.3 MB
Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-tfYAGBIR_Ws.mp4
12.1 MB
Part 01-Module 12-Lesson 01_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.mp4
12.1 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/11. Gradient Descent-Math-7sxA5Ap8AWM.mp4
11.8 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/07. Tile Coding-BRs7AnTZ_8k.mp4
11.6 MB
Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.mp4
11.3 MB
Part 02-Module 04-Lesson 04_Actor-Critic Methods/05. RL M2L4 05 Advantage Function RENDER V1 V2-vpLmzKqcgfc.mp4
11.2 MB
Part 01-Module 11-Lesson 01_Clustering/11. K-Means Clustering Visualization 2-fQXXa-CAoS0.mp4
11.0 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/03. Monte Carlo Learning-qOviWYwcvsg.mp4
10.9 MB
Part 02-Module 04-Lesson 04_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.mp4
10.9 MB
Part 01-Module 13-Lesson 01_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.mp4
10.8 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/09. Coarse Coding-Uu1J5KLAfTU.mp4
10.8 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/20. Image Augmentation in Keras-odStujZq3GY.mp4
10.8 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.mp4
10.8 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/05. Naive Bayes Quiz-jsLkVYXmr3E.mp4
10.6 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.mp4
10.6 MB
Part 02-Module 04-Lesson 04_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.mp4
10.5 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Elevator Pitch-0QtgTG49E9I.mp4
10.5 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/10. Cumulative Reward-ysriH65lV9o.mp4
10.4 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/14. Summary-MTEBk43oByU.mp4
10.4 MB
Part 01-Module 15-Lesson 01_Random Projection and ICA/10. L6 6 ICA Applications MAIN V1 V1 V1-th12mTv1B7g.mp4
10.4 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/16. Neural Networks-xFu1_2K2D2U.mp4
10.2 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/23. Conclusion-hJEuaOUu2yA.mp4
10.2 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/06. TD Prediction Action Values-1c029-7_9GA.mp4
10.2 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/12. SVM 10 Polynomial Kernel 2 V2-9RfFvZ9DIRg.mp4
10.2 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.mp4
10.1 MB
Part 02-Module 03-Lesson 01_Introduction to RL/04. OpenAI Gym-MktEOWp3QLg.mp4
9.9 MB
Part 01-Module 10-Lesson 04_Naive Bayes/10. SL NB 09 Bayesian Learning 3 V1 V4-u-Hj4RsJn1o.mp4
9.8 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/16. SVM 14 RBF Kernel 3 V1-DctkE8kaWPY.mp4
9.7 MB
Part 01-Module 10-Lesson 03_Decision Trees/13. Information Gain-k9iZL53PAmw.mp4
9.7 MB
Part 01-Module 07-Lesson 01_Model Selection/03. Model-Complexity-Graph Solution 2-5pWHGkNyRhA.mp4
9.7 MB
Part 01-Module 15-Lesson 01_Random Projection and ICA/01. L6 1 Random Projection MAIN V1 V1 V1-Iat1a8mzI-Y.mp4
9.6 MB
Part 01-Module 10-Lesson 03_Decision Trees/15. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.mp4
9.6 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/23. Visualizando CNNs-mnqS_EhEZVg.mp4
9.6 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/02. Solving Problems - Big And Small-WHcRQMGSbqg.mp4
9.6 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.mp4
9.6 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.mp4
9.5 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/01. Intro to Deep Q-Learning-o3cmuUDhP3I.mp4
9.5 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.mp4
9.4 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/12. Kernel Functions-RdkPVYyVOvU.mp4
9.3 MB
Part 01-Module 10-Lesson 01_Linear Regression/22. Regularization-PyFNIcsNma0.mp4
9.2 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/18. CNNs in Keras Practical Example-faFvmGDwXX0.mp4
9.1 MB
Part 02-Module 04-Lesson 04_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.mp4
9.1 MB
Part 01-Module 10-Lesson 04_Naive Bayes/02. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.mp4
8.9 MB
Part 03-Module 04-Lesson 01_Deep Neural Networks/01. Mat HS-9P7UPWFu8w8.mp4
8.9 MB
Part 02-Module 03-Lesson 01_Introduction to RL/02. Applications-CV6B84mKRNM.mp4
8.9 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/22. Hierarchical Clustering-1PldDT8AwMA.mp4
8.9 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/04. Convolutional Networks-ISHGyvsT0QY.mp4
8.8 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.mp4
8.8 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.mp4
8.8 MB
Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.mp4
8.7 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/26. Conclusion-WhpE_8sTt-0.mp4
8.6 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.mp4
8.5 MB
Part 01-Module 11-Lesson 01_Clustering/16. Counterintuitive Clusters-StmEUgT1XSY.mp4
8.5 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/22. Groundbreaking CNN Architectures-ddrB-mhMfkY.mp4
8.5 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/08. Goals and Rewards, Part 2-pVIFc72VYH8.mp4
8.4 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/10. Convolutional Layers-h5R_JvdUrUI.mp4
8.4 MB
Part 01-Module 10-Lesson 03_Decision Trees/10. Entropy Formula-w73JTBVeyjE.mp4
8.4 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/12. Stride and Padding-0r9o8hprDXQ.mp4
8.4 MB
Part 01-Module 15-Lesson 01_Random Projection and ICA/05. L6 4 ICA Algorithm V2 V1-xlhd5UWk_-E.mp4
8.3 MB
Part 01-Module 13-Lesson 01_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.mp4
8.2 MB
Part 02-Module 03-Lesson 01_Introduction to RL/03. The Setting-nh8Gwdu19nc.mp4
8.1 MB
Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-MEtIAGKweXU.mp4
8.1 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/08. M2L3 08 V1-og3W6CXn1F0.mp4
8.0 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/07. TD Control Sarsa(0)-LkFkjfsRpXc.mp4
8.0 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/13. Regularization-ndYnUrx8xvs.mp4
7.9 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/img/chess-game.jpg
7.9 MB
Part 02-Module 02-Lesson 01_Neural Networks/02. Introduction-tn-CrUTkCUc.mp4
7.9 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.mp4
7.8 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/29. Inception Module-SlTm03bEOxA.mp4
7.8 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/08. M1 L1 C05 V3 No Slack-OH-fVUpoyZDyGE.mp4
7.8 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/03. Logistic Regression - Solution-1iNylA3fJDs.mp4
7.7 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/02. The Setting, Revisited-V6Q1uF8a6kA.mp4
7.7 MB
Part 01-Module 11-Lesson 01_Clustering/03. Clustering Movies-g8PKffm8IRY.mp4
7.7 MB
Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-HyjBus7S2gY.mp4
7.6 MB
Part 01-Module 10-Lesson 04_Naive Bayes/05. SL NB 04 Bayes Theorem V1 V2-nVbPJmf53AI.mp4
7.6 MB
Part 02-Module 02-Lesson 01_Neural Networks/14. Error Functions-jfKShxGAbok.mp4
7.6 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/13. Wrap Up-x6JggcDTcys.mp4
7.6 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/11. Optimal Policies-2rguYpVyCto.mp4
7.5 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/11. SVM 09 Polynomial Kernel 1 V1-8t2tVDHNBnk.mp4
7.4 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/10. SVM 08 The C Parameter V2-6CxPhVo0hRw.mp4
7.4 MB
Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.mp4
7.4 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.mp4
7.3 MB
Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.mp4
7.3 MB
Part 02-Module 03-Lesson 01_Introduction to RL/05. Resources-_YPqfAnCqtk.mp4
7.3 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.mp4
7.3 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.mp4
7.3 MB
Part 01-Module 11-Lesson 01_Clustering/12. K-Means Clustering Visualization 3-WfwX3B4d8_I.mp4
7.3 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/07. Goals and Rewards, Part 1-XPnj3Ya3EuM.mp4
7.2 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/14. MDPs, Part 2-CUTtQvxKkNw.mp4
7.2 MB
Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.mp4
7.2 MB
Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.mp4
7.0 MB
Part 01-Module 06-Lesson 01_Evaluation Metrics/12. ROC Curve-2Iw5TiGzJI4.mp4
7.0 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/18. ROC Curve-2Iw5TiGzJI4.mp4
7.0 MB
Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.mp4
7.0 MB
Part 02-Module 02-Lesson 01_Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp4
6.9 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/09. Action-Value Functions-KJLaRfOOPGA.mp4
6.9 MB
Part 01-Module 07-Lesson 01_Model Selection/01. 04 L Types Of Errors-Twf1qnPZeSY.mp4
6.9 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/06. Backpropagation V2-1SmY3TZTyUk.mp4
6.8 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/08. MLND - Unsupervised Learning - L3 08 Overview Of The Expectation Maximization Algorithm MAIN V1 V1-XdQfFnnj5Xo.mp4
6.7 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/19. Kernel Method Answer-dRFd6HaAXys.mp4
6.7 MB
Part 01-Module 02-Lesson 01_Nanodegree Career Services/img/feb-26-2019-16-19-56.gif
6.6 MB
Part 01-Module 10-Lesson 03_Decision Trees/04. Recommending Apps-nEvW8B1HNq4.mp4
6.6 MB
Part 01-Module 13-Lesson 01_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.mp4
6.6 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/01. Introduction-ek2PD9RDrWw.mp4
6.5 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/03. How Computers Interpret Images-V4f6p6uRhu8.mp4
6.5 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/12. Logistic Regression Answer-JuAJd9Qvs6U.mp4
6.4 MB
Part 02-Module 04-Lesson 04_Actor-Critic Methods/03. RL M2L4 03 Two Function Approximators V1-37KQEgLaLfw.mp4
6.4 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/01. M0 L3 C01 Intro- V3 No Slack-OH-5IlSH-eoPAU.mp4
6.4 MB
Part 01-Module 10-Lesson 04_Naive Bayes/08. SL NB 07 Q Bayesian Learning 1 V1 V4-J4BmsKXPnkA.mp4
6.4 MB
Part 01-Module 06-Lesson 01_Evaluation Metrics/10. 08 F1 Score SC V1-TRzBeL07fSg.mp4
6.3 MB
Part 01-Module 15-Lesson 01_Random Projection and ICA/04. L6 3 ICA V1 V1-ae94x-1JDzg.mp4
6.3 MB
Part 01-Module 07-Lesson 01_Model Selection/05. Learning Curves SC V1-ZNhnNVKl8NM.mp4
6.3 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.mp4
6.3 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/08. Optimality-j231aRV74QM.mp4
6.3 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/04. SVM 03 Error Function V1-l-ahImxoi-U.mp4
6.2 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.mp4
6.1 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/15. Pooling Layers-OkkIZNs7Cyc.mp4
6.1 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/01. What Is Deep Learning-INt1nULYPak.mp4
6.1 MB
Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-gg7SAMMl4kM.mp4
6.0 MB
Part 02-Module 02-Lesson 01_Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.mp4
6.0 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/06. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp4
6.0 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/07. When do MLPs (not) work well-deMeuLdZN3Q.mp4
5.8 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.mp4
5.8 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/19. 21 L Measuring Performance-byP0DJImOSk.mp4
5.8 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/05. Categorical Cross-Entropy-3sDYifgjFck.mp4
5.7 MB
Part 01-Module 10-Lesson 03_Decision Trees/06. Student Admissions-TdgBi6LtOB8.mp4
5.7 MB
Part 01-Module 10-Lesson 04_Naive Bayes/06. SL NB 05 Q False Positives V1 V2-ngA6v09eP08.mp4
5.7 MB
Part 01-Module 07-Lesson 01_Model Selection/02. Model Complexity Graph-Question-YS5OQCA5cLY.mp4
5.7 MB
Part 01-Module 10-Lesson 02_Perceptron Algorithm/01. Perception Algorithm V2-ebIlG6Pqwas.mp4
5.6 MB
Part 02-Module 02-Lesson 01_Neural Networks/15. Discrete vs. Continuous-Rm2KxFaPiJg.mp4
5.6 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/05. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp4
5.6 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/05. State-Value Functions-llakAjwox_8.mp4
5.5 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/06. Model Validation in Keras-002jNXSM6CU.mp4
5.5 MB
Part 01-Module 13-Lesson 01_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.mp4
5.4 MB
Part 01-Module 10-Lesson 01_Linear Regression/06. Absolute Trick-DJWjBAqSkZw.mp4
5.4 MB
Part 02-Module 03-Lesson 01_Introduction to RL/01. Introduction-6jSFl5kxIBs.mp4
5.4 MB
Part 01-Module 10-Lesson 04_Naive Bayes/11. MLND SL NB Naive Bayes Algorithm-CQBMB9jwcp8.mp4
5.4 MB
Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-5j6VZr8sHo8.mp4
5.4 MB
Part 01-Module 10-Lesson 02_Perceptron Algorithm/06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp4
5.4 MB
Part 02-Module 02-Lesson 01_Neural Networks/07. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp4
5.4 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/15. SVM 13 RBF Kernel 2 V1-ozl9UWVP0MI.mp4
5.3 MB
Part 01-Module 06-Lesson 01_Evaluation Metrics/01. Confusion Matrix-Question 1-9GLNjmMUB_4.mp4
5.3 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/24. Confusion Matrix-Question 1-9GLNjmMUB_4.mp4
5.3 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/18. Explore the Design Space-FG7M9tWH2nQ.mp4
5.2 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/01. M2L3 01 V1-YOSREyp04HA.mp4
5.2 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/13. Non-Linear Function Approximation-rITnmpD2mN8.mp4
5.2 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/01. Introduction-W2EP3riQSus.mp4
5.2 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/11. Model Complexity Graph-NnS0FJyVcDQ.mp4
5.1 MB
Part 02-Module 02-Lesson 01_Neural Networks/23. Error Function-V5kkHldUlVU.mp4
5.1 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/02. Decision Trees Question-1RonLycEJ34.mp4
5.1 MB
Part 01-Module 10-Lesson 03_Decision Trees/02. MLND SL DT 01 Recommending Apps 1 MAIN V3-uI_yNrqqKVg.mp4
5.0 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Combinando modelos-Boy3zHVrWB4.mp4
5.0 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/02. 02 Skin Cancer V4-70jGZeiTNgk.mp4
5.0 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/04. Another Gridworld Example-n9SbomnLb-U.mp4
4.9 MB
Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.mp4
4.9 MB
Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-4Fkfu37el_k.mp4
4.9 MB
Part 01-Module 05-Lesson 01_Training and Testing Models/01. 01 Intro-4C4PuJANIdE.mp4
4.9 MB
Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.mp4
4.8 MB
Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.mp4
4.8 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/10. Linear Regression Answer-L5QBqYDNJn0.mp4
4.7 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/04. MLPs For Image Classification-TIFStebu530.mp4
4.6 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/06. The Reward Hypothesis-uAqNwgZ49JE.mp4
4.6 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/02. MLND - Unsupervised Learning - L3 2 Gaussian Mixture Model Clustering MAIN V1 V2-Y_methsXoFA.mp4
4.5 MB
Part 01-Module 10-Lesson 03_Decision Trees/08. Entropy Formula-iZiSYrOKvpo.mp4
4.5 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/13. TD Control Expected Sarsa-kEKupCyU0P0.mp4
4.5 MB
Part 01-Module 10-Lesson 01_Linear Regression/08. Gradient Descent-4s4x9h6AN5Y.mp4
4.5 MB
Part 02-Module 02-Lesson 01_Neural Networks/20. Cross Entropy 1-iREoPUrpXvE.mp4
4.4 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/14. Dropout-Ty6K6YiGdBs.mp4
4.4 MB
Part 01-Module 10-Lesson 03_Decision Trees/03. MLND SL DT 02 Recommending Apps 2 MAIN V3-KSrIYqKZwCA.mp4
4.4 MB
Part 01-Module 13-Lesson 01_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.mp4
4.4 MB
Part 01-Module 10-Lesson 03_Decision Trees/05. MLND SL DT 04 Q Student Admissions V3 MAIN V1-MOa335cQGI4.mp4
4.4 MB
Part 02-Module 02-Lesson 01_Neural Networks/22. DL 27 Multi-Class Cross Entropy 2 Fix-keDswcqkees.mp4
4.3 MB
Part 02-Module 03-Lesson 03_The RL Framework The Solution/06. Bellman Equations-UgIaDMvSdUo.mp4
4.3 MB
Part 01-Module 05-Lesson 01_Training and Testing Models/02. 02 Intro SC V1-mIgABrjJVBY.mp4
4.3 MB
Part 01-Module 11-Lesson 01_Clustering/16. Counterintuitive Clusters-aveIz1JYeAg.mp4
4.3 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/18. Normalized Inputs And Initial Weights-WaHQ9-UXIIg.mp4
4.3 MB
Part 02-Module 02-Lesson 01_Neural Networks/16. DL 18 Q Softmax V2-RC_A9Tu99y4.mp4
4.2 MB
Part 01-Module 10-Lesson 08_Supervised Learning Project/01. ML Charity Project-aVodYHcOB8U.mp4
4.2 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/07. Quick Fixes-Lb9e2KemR6I.mp4
4.2 MB
Part 01-Module 12-Lesson 01_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.mp4
4.2 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/18. Batch vs Stochastic Gradient Descent-2p58rVgqsgo.mp4
4.1 MB
Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.mp4
4.1 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/21. 30 L Stochastic Gradient Descent-U9iEGUd9kJ0.mp4
4.1 MB
Part 01-Module 10-Lesson 01_Linear Regression/01. Welcome To Linear Regression-zxZkTkM34BY.mp4
4.1 MB
Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-xJtmPbEfpFo.mp4
4.1 MB
Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-PRjmvj6Vubs.mp4
4.1 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/13. MDPs, Part 1-NBWbluSbxPg.mp4
4.0 MB
Part 01-Module 10-Lesson 01_Linear Regression/11. Minimizing Error Functions-RbT2TXN_6tY.mp4
4.0 MB
Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.mp4
4.0 MB
Part 01-Module 10-Lesson 02_Perceptron Algorithm/04. Linear Boundaries-X-uMlsBi07k.mp4
4.0 MB
Part 02-Module 02-Lesson 01_Neural Networks/05. Linear Boundaries-X-uMlsBi07k.mp4
4.0 MB
Part 02-Module 02-Lesson 01_Neural Networks/18. Maximum Likelihood 2-6nUUeQ9AeUA.mp4
4.0 MB
Part 02-Module 02-Lesson 01_Neural Networks/24. Gradient Descent-rhVIF-nigrY.mp4
3.9 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/04. Good GitHub repository-qBi8Q1EJdfQ.mp4
3.9 MB
Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. 07 Perceptron Algorithm Trick-lif_qPmXvWA.mp4
3.8 MB
Part 02-Module 02-Lesson 01_Neural Networks/10. 07 Perceptron Algorithm Trick-lif_qPmXvWA.mp4
3.8 MB
Part 01-Module 05-Lesson 01_Training and Testing Models/08. MLND Turning Paramaters-eSv2lPcnRM0.mp4
3.8 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/01. Introducing Luis-nto-stLuN6M.mp4
3.8 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.mp4
3.8 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/16. 17 L Transition Into Practical Aspects Of Learning-bKqkRFOOKoA.mp4
3.8 MB
Part 01-Module 10-Lesson 06_Ensemble Methods/06. MLND SL EM 06 Weighting The Models MAIN V2-unCJ_ifVquU.mp4
3.7 MB
Part 02-Module 02-Lesson 01_Neural Networks/13. Error Functions-YfUUunxWIJw.mp4
3.7 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.24-pm.png
3.7 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.24-pm.png
3.7 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-ZwMY5rAAd7Q.mp4
3.6 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/23. What Is The Neural Network Looking At-qN-rvoxPbBw.mp4
3.6 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/24. Neural Network Regression-aUJCBqBfEnI.mp4
3.6 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/02. Logistic Regression - Question-kSs6O3R7JUI.mp4
3.6 MB
Part 01-Module 07-Lesson 01_Model Selection/08. Grid Search SC V1-zDw-ZGiHW5I.mp4
3.6 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/15. Backpropagation-MZL97-2joxQ.mp4
3.6 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/20. 29 L Optimizing A Logistic Classifier-U_7nO1dm2tY.mp4
3.6 MB
Part 01-Module 10-Lesson 06_Ensemble Methods/01. MLND SL EM 01 Intro V1 MAIN V2-5v9KqIo6CFE.mp4
3.5 MB
Part 01-Module 12-Lesson 01_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.mp4
3.5 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/03. GitHub profile important items-prvPVTjVkwQ.mp4
3.5 MB
Part 01-Module 06-Lesson 01_Evaluation Metrics/13. Regression-Metrics-906P4BPnl9A.mp4
3.5 MB
Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.mp4
3.5 MB
Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-iCTPBcowJRY.mp4
3.5 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/06. Calculating The Gradient 1 -tVuZDbUrzzI.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/29. Neural Networks Outro V2-pwA5shUkRVc.mp4
3.5 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/15. Participating in open source projects 2-elZCLxVvJrY.mp4
3.5 MB
Part 01-Module 10-Lesson 01_Linear Regression/07. Square Trick-AGZEq-yQgRM.mp4
3.4 MB
Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.mp4
3.4 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/15. SVM Answer-JrUtTwfnsfM.mp4
3.4 MB
Part 01-Module 10-Lesson 04_Naive Bayes/01. Naive Bayes Intro V2-vNOiQXghgRY.mp4
3.4 MB
Part 02-Module 02-Lesson 01_Neural Networks/28. Gradient Descent Vs Perceptron Algorithm-uL5LuRPivTA.mp4
3.4 MB
Part 01-Module 13-Lesson 01_PCA/16. Compression While Preserving Information-_TJeoCTDykE.mp4
3.3 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/28. 1x1 Convolutions-Zmzgerm6SjA.mp4
3.3 MB
Part 01-Module 13-Lesson 01_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.mp4
3.3 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Layers-pg99FkXYK0M.mp4
3.3 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/14. 16 L Minimizing Cross-Entropy-YrDMXFhvh9E.mp4
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Part 01-Module 01-Lesson 02_What is Machine Learning/17. Kernel Method Quiz-x0JqH6-Dhvw.mp4
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/06. RL M2L4 06 Actor Critic With Advantage RENDER V1 V1-Bwd2OF7hJXQ.mp4
3.2 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.02-pm.png
3.2 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.02-pm.png
3.2 MB
Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.mp4
3.2 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/25. Confusion Matrix-3rpN-YYlfes.mp4
3.2 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/12. Reflect on your commit messages-_0AHmKkfjTo.mp4
3.2 MB
Part 02-Module 02-Lesson 01_Neural Networks/19. Quiz - Cross 1--xxrisIvD0E.mp4
3.2 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/06. M2L3 06 V1-RMjdQkl6CqE.mp4
3.2 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.mp4
3.1 MB
Part 01-Module 01-Lesson 02_What is Machine Learning/11. Logistic Regression Question-wQXKdeVHTmc.mp4
3.1 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/10. Training Optimization-UiGKhx9pUYc.mp4
3.1 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/03. SVM 02 Minimizing Distances V1-mNKk2dBsNGA.mp4
3.1 MB
Part 02-Module 03-Lesson 02_The RL Framework The Problem/01. Introduction-X_9l_ZqXXBA.mp4
3.0 MB
Part 02-Module 02-Lesson 04_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.08.11-pm.png
3.0 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.08.11-pm.png
3.0 MB
Part 01-Module 10-Lesson 02_Perceptron Algorithm/09. Perceptron Algorithm Pseudocode-p8Q3yu9YqYk.mp4
3.0 MB
Part 02-Module 02-Lesson 01_Neural Networks/11. Perceptron Algorithm Pseudocode-p8Q3yu9YqYk.mp4
3.0 MB
Part 01-Module 10-Lesson 06_Ensemble Methods/07. MLND SL EM 07 Weighting The Models 3 V1 MAIN V1-fecp5nmetws.mp4
3.0 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/05. The Data-2RLbbV7MQNA.mp4
3.0 MB
Part 03-Module 03-Lesson 01_Intro to Neural Networks/14. Multilayer perceptrons-Rs9petvTBLk.mp4
3.0 MB
Part 01-Module 10-Lesson 01_Linear Regression/18. Closed Form Solution-G3fRVgLa5gI.mp4
3.0 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/11. Solution Random Vs Preinitialized Thoughts-sOuoRZRKDzs.mp4
3.0 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/04. 29 Neural Network Architecture 2-FWN3Sw5fFoM.mp4
3.0 MB
Part 01-Module 13-Lesson 01_PCA/17. Composite Features-0ZBp8oWySAc.mp4
3.0 MB
Part 01-Module 11-Lesson 01_Clustering/14. Some challenges of k-means-e2CdlG5P4WA.mp4
3.0 MB
Part 01-Module 11-Lesson 01_Clustering/04. How Many Clusters-R6oIvdBtsZw.mp4
2.9 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/13. Participating in open source projects-OxL-gMTizUA.mp4
2.9 MB
Part 01-Module 13-Lesson 01_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.mp4
2.9 MB
Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.mp4
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.mp4
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Part 02-Module 03-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/open-agent-monitor-main.gif
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/07. DL 08 AND And OR Perceptrons-Y-ImuxNpS40.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/08. DL 08 AND And OR Perceptrons-Y-ImuxNpS40.mp4
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/08. Training Your Logistic Classifier-WQsdr1EJgz8.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.mp4
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Part 01-Module 13-Lesson 01_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/11. 09 Quiz Fbeta Score SC V1-KSswld4_9bY.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/16. Higher Dimensions--UvpQV1qmiE.mp4
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Part 01-Module 10-Lesson 06_Ensemble Methods/08. MLND SL EM 08 Combining The Models V1 MAIN V1-1GxscvKU2Ic.mp4
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Part 01-Module 10-Lesson 04_Naive Bayes/03. SL NB 02 Known And Inferred V1 V2-DrYfZXiDLQI.mp4
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/05. 09 Higher Dimensions-eBHunImDmWw.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/06. 09 Higher Dimensions-eBHunImDmWw.mp4
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Part 03-Module 04-Lesson 01_Deep Neural Networks/11. Dropout RENDER-6DcImJS8uV8.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/29. Conclusion-wOiUQDgGD9E.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/09. Mean Absolute Error-vLKiY0Ehors.mp4
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Part 03-Module 04-Lesson 01_Deep Neural Networks/05. Training a Deep Learning Network-CsB7yUtMJyk.mp4
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Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.mp4
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Part 01-Module 10-Lesson 06_Ensemble Methods/04. MLND SL EM 04 Weighting The Data MAIN V1 V2-O-hh_x0iYW8.mp4
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Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.mp4
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.mp4
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/10. Gradient Descent-29PmNG7fuuM.mp4
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Part 01-Module 01-Lesson 02_What is Machine Learning/08. Gradient Descent-BEC0uH1fuGU.mp4
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-U3FUxkm1MxI.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/22. Visualization-aGIGB4Ta3_A.mp4
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Part 01-Module 10-Lesson 05_Support Vector Machines/01. Support Vector Machine V2-LBmM6pZCrI0.mp4
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.mp4
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/04. Gridworld Example-XeHBmPFqTsE.mp4
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Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/03. Accuracy-s6SfhPTNOHA.mp4
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Part 01-Module 10-Lesson 06_Ensemble Methods/02. MLND SL EM 02 Bagging V1 MAIN V1-9L_B0Jcio3c.mp4
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Part 01-Module 10-Lesson 06_Ensemble Methods/11. Supervised Learning Outro V2-7X2SDqzGrdU.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/17. 16 Solution Diagnosing Cancer V3-IJYvt2ssUFk.mp4
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/22. 31 L Momentum And Learning Rate Decay-O3QYdmQjXds.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/17. Other Activation Functions-kA-1vUt6cvQ.mp4
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Part 01-Module 01-Lesson 02_What is Machine Learning/20. Recap and Challenge-ecREasTrKu4.mp4
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Part 01-Module 01-Lesson 02_What is Machine Learning/07. Naive Bayes Answer-YKN-fjuZ1VU.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.mp4
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/08. 06 Precision SC V1-q2wVorBfefU.mp4
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/23. 32 L Parameter Hyperspace!-5a3-iIhdguc.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/07. Answer False Negatives And Positives-KOytJL1lvgg.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/06. 04 Quiz False Negatives And Positives SC V1-_ytP9zIkziw.mp4
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/03. Statistical Invariance-0Hr5YwUUhr0.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/04. Medical Classification-RCOSP60dV7U.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/26. Keras Lab-a50un22BsLI.mp4
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Part 01-Module 10-Lesson 06_Ensemble Methods/03. MLND SL EM 03 AdaBoost V1 MAIN V1-HD6SRBWKGUE.mp4
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Part 01-Module 10-Lesson 03_Decision Trees/12. MLND SL DT 10 Q Information Gain MAIN V1-tVLOLPEtLFw.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/05. When Accuracy Wont Work-r0-O-gIDXZ0.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/09. 07 Recall SC V1-0n5wUZiefkQ.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/21. Momentum-r-rYz_PEWC8.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.mp4
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/02. Exemplo de classificação-Dh625piH7Z0.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/03. Exemplo de classificação-Dh625piH7Z0.mp4
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/01. Apresentando Alexis-38ExGpdyvJI.mp4
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Part 01-Module 07-Lesson 01_Model Selection/13. MLND Outro-sFvMBncQjr8.mp4
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Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.mp4
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Part 02-Module 03-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/run-main.gif
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-xSQTzAeeoEc.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.mp4
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. Perceptron Algorithm--zhTROHtscQ.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/10. Perceptron Algorithm--zhTROHtscQ.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Multiclass Classification-uNTtvxwfox0.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/10. Mean Squared Error-MRyxmZDngI4.mp4
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/01. Intro to CNNs-B61jxZ4rkMs.mp4
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Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.mp4
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Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.mp4
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Part 01-Module 10-Lesson 04_Naive Bayes/09. SL NB 08 S Bayesian Learning 2 V1 V6-3rIYZgCXVXY.mp4
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Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.mp4
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Part 01-Module 01-Lesson 02_What is Machine Learning/09. Linear Regression Question-sf51L0RN6zc.mp4
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Part 01-Module 07-Lesson 01_Model Selection/04. KFold Cross Validation V3 V1-9W6o6eWGi-0.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/23. Error Functions Around the World-34AAcTECu2A.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/05. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.mp4
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Part 01-Module 10-Lesson 05_Support Vector Machines/09. SVM 07 Error Function V1-A1wbrcSYc1c.mp4
1.8 MB
Part 01-Module 13-Lesson 01_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.mp4
1.8 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/img/screen-shot-2018-09-21-at-11.36.43-am.png
1.8 MB
Part 02-Module 02-Lesson 01_Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.mp4
1.7 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/img/skin-disease-classes.png
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/03. 分类问题 2 -46PywnGa_cQ.mp4
1.7 MB
Part 02-Module 02-Lesson 01_Neural Networks/04. 分类问题 2 -46PywnGa_cQ.mp4
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-lS5DfbsWH34.mp4
1.7 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/08. Convolutions Cont.-utOv-BKI_vo.mp4
1.7 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-ncFtwW5urHk.mp4
1.7 MB
Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.mp4
1.7 MB
Part 01-Module 11-Lesson 01_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.mp4
1.7 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/10. 10 Quiz Random Vs Preinitiliazed Weights V3-DRC1e4XGl2M.mp4
1.7 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/14. Solution Sensitivty And Specificity-GBZjyeMjKxc.mp4
1.7 MB
Part 01-Module 10-Lesson 01_Linear Regression/23. Conclusion-pyeojf0NniQ.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/img/lesions.png
1.6 MB
Part 01-Module 03-Lesson 01_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.48.22-pm.png
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Part 03-Module 04-Lesson 01_Deep Neural Networks/09. Regularization-QcJBhbuCl5g.mp4
1.6 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/01. Introduction-ZCpXvVdIdnY.mp4
1.6 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.mp4
1.6 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/03. Survival Rate-QPlp3NeGuSk.mp4
1.6 MB
Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-FpQm_dYA9LM.mp4
1.6 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/img/frozen-lake-6.jpg
1.6 MB
Part 02-Module 02-Lesson 01_Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.mp4
1.6 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/08. Solution Data Challenges-1z3o4niQuNg.mp4
1.6 MB
Part 01-Module 10-Lesson 01_Linear Regression/02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.mp4
1.6 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/06. 06 Image Challenge V3-Efnoj1KNPHw.mp4
1.5 MB
Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.mp4
1.5 MB
Part 02-Module 02-Lesson 03_Deep Neural Networks/06. Chain Rule-YAhIBOnbt54.mp4
1.5 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/03. Let'S Get Started-ySIDqaXLhHw.mp4
1.5 MB
Part 01-Module 10-Lesson 04_Naive Bayes/12. MLND SL NB Solution Naive Bayes Algorithm-QDj3xzjuYmo.mp4
1.5 MB
Part 01-Module 07-Lesson 01_Model Selection/12. Outro SC V1-YD1grQje9fw.mp4
1.5 MB
Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.mp4
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Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.mp4
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Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-FY0DXe0lfrI.mp4
1.4 MB
Part 02-Module 02-Lesson 01_Neural Networks/12. Non-Linear Regions-B8UrWnHh1Wc.mp4
1.4 MB
Part 03-Module 02-Lesson 01_Intro to TensorFlow/07. Supervised Classification-XTGsutypAPE.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/16. Vanishing Gradient-W_JJm_5syFw.mp4
1.4 MB
Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.mp4
1.4 MB
Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.mp4
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Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.mp4
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Part 03-Module 04-Lesson 01_Deep Neural Networks/12. Dropout Pt. 2-8nG8zzJMbZw.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/09. Training The Neural Network-HwiI-UXUx-M.mp4
1.3 MB
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/img/arch.png
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Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.mp4
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/img/convolutionalnetworksquiz.png
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/07. Feature-Map-Sizes-Solution-W4xtf8LTz1c.mp4
1.2 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.mp4
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Part 01-Module 15-Lesson 01_Random Projection and ICA/03. L6 2 Random Projection Impl MAINv1 V1 V1-5DhvurLgRII.mp4
1.2 MB
Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.mp4
1.2 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/02. Continuous Perceptrons-07-JJ-aGEfM.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/03. Non-Linear Models-HWuBKCZsCo8.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/04. Fitting A Line-gkdoknEEcaI.mp4
1.2 MB
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/20. Solution ROC Curve-sdUUf6RRmXI.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.mp4
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Part 01-Module 06-Lesson 01_Evaluation Metrics/02. Confusion-Matrix-Solution-ywwSzyU9rYs.mp4
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Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-9J3IwQFXveI.mp4
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Part 01-Module 13-Lesson 01_PCA/03. One-Dimensional, or Two-QsncWsyboFk.mp4
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Part 01-Module 12-Lesson 01_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.mp4
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Part 01-Module 15-Lesson 01_Random Projection and ICA/07. L6 5 ICA Implementation V1 V1-fZGxYfJmKaE.mp4
1.1 MB
Part 01-Module 10-Lesson 06_Ensemble Methods/05. MLND SL EM 05 Weighting The Models MAIN V1-wn6K536dPLc.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/12. DL 53 Q Regularization-KxROxcRsHL8.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/03. Solution Housing Prices-uhdTulw9-Nc.mp4
1.0 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/img/statevalue.png
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Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-nvLhUSSUhiY.mp4
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/img/logistic-regression-quiz.png
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Part 01-Module 10-Lesson 01_Linear Regression/21. Polynomial Regression-DBhWG-PagEQ.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/09. 为何是神经网络-zAkzOZntK6Y.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/05. Moving A Line-8EIHFyL2Log.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/19. Learning Rate-TwJ8aSZoh2U.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/img/nature.png
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/14. DLND REG 13 Absolute Vs Squared Error 3 V1 (1)-bIVGf_dDkrY.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.mp4
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Part 01-Module 12-Lesson 01_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.mp4
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Part 02-Module 02-Lesson 03_Deep Neural Networks/15. Local Minima-gF_sW_nY-xw.mp4
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/02. Color-Question-BdQccpMwk80.mp4
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Part 02-Module 03-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/open-terminal.gif
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Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-uC1Xwc7warg.mp4
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Part 01-Module 11-Lesson 01_Clustering/09. Handoff to Katie-knrPsGtpyQY.mp4
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Part 01-Module 11-Lesson 01_Clustering/img/sebastian-katie-jay.png
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/img/screen-shot-2018-02-23-at-5.00.25-pm.png
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/img/student-quiz.png
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Part 02-Module 02-Lesson 01_Neural Networks/img/student-quiz.png
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Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.mp4
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/12. 13 L One Hot Encoding-phYsxqlilUk.mp4
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/img/screen-shot-2017-10-04-at-4.58.58-pm.png
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/img/6509638772.gif
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.mp4
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Part 01-Module 13-Lesson 01_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/14. DLND REG 12 Absolute Vs Squared Error 2 V1 (1)-7El1OH17Oi4.mp4
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Part 01-Module 10-Lesson 01_Linear Regression/14. Absolute Vs Squared Error-csvdjaqt1GM.mp4
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Part 01-Module 10-Lesson 06_Ensemble Methods/img/screen-shot-2018-01-03-at-2.20.30-pm.png
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/17. Numerical Stability-_SbGcOS-jcQ.mp4
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Part 02-Module 03-Lesson 04_Dynamic Programming/img/actionvalue.png
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Part 01-Module 07-Lesson 01_Model Selection/img/models.png
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/img/screen-shot-2017-09-24-at-4.28.04-pm.png
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/img/go.jpg
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Part 02-Module 01-Lesson 01_Welcome to Advanced Machine Learning/img/thumbs-up.jpg
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/img/and-to-or.png
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Part 02-Module 02-Lesson 01_Neural Networks/img/and-to-or.png
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Part 03-Module 04-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.mp4
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/img/profile-pics.jpg
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Part 01-Module 01-Lesson 02_What is Machine Learning/13. SVM Question-Fwnjx0s_AIw.mp4
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Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-FZVBF1HR4U0.mp4
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/img/cat-3.png
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Part 01-Module 06-Lesson 01_Evaluation Metrics/04. Accuracy 2-ueYCLfd_aNQ.mp4
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.mp4
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Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-bAZJT4xHiXM.mp4
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Part 02-Module 04-Lesson 05_Teach a Quadcopter How to Fly/img/submit-workspace.png
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Part 01-Module 12-Lesson 01_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.mp4
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/07. DL 09 XOR Perceptron--z9K49fdE3g.mp4
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Part 02-Module 02-Lesson 01_Neural Networks/08. DL 09 XOR Perceptron--z9K49fdE3g.mp4
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Part 02-Module 01-Lesson 01_Welcome to Advanced Machine Learning/05. Deadline Policy.html
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Part 01-Module 09-Lesson 01_Predicting Boston Housing Prices/Project Rubric - Predicting Boston Housing Prices.html
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/01. Get Opportunities with LinkedIn.html
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/02. OpenAI Gym BlackjackEnv.html
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/07. Quiz Data Challenges.html
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/05. Use Your Elevator Pitch on LinkedIn.html
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/03. How Computers Interpret Images.html
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/08. Work Experiences Accomplishments.html
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/16. Quiz Diagnosing Cancer.html
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Part 01-Module 10-Lesson 01_Linear Regression/02. Quiz Housing Prices.html
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Part 01-Module 11-Lesson 01_Clustering/index.html
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Part 03-Module 04-Lesson 01_Deep Neural Networks/index.html
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Part 01-Module 07-Lesson 01_Model Selection/index.html
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Part 02-Module 04-Lesson 02_Deep Q-Learning/index.html
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/index.html
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Part 01-Module 06-Lesson 01_Evaluation Metrics/index.html
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Part 01-Module 15-Lesson 01_Random Projection and ICA/index.html
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Part 02-Module 04-Lesson 05_Teach a Quadcopter How to Fly/index.html
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Part 01-Module 05-Lesson 01_Training and Testing Models/index.html
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/02. Policies-hc3LrvaC13U.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/07. Entropy-piLpj1V1HEk.en.vtt
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/18. CNNs in Keras Practical Example-faFvmGDwXX0.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/19. Kernel Method Answer-dRFd6HaAXys.en.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/index.html
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/24. Confusion Matrix-Question 1-9GLNjmMUB_4.pt-BR.vtt
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Part 01-Module 10-Lesson 08_Supervised Learning Project/index.html
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Part 01-Module 17-Lesson 01_Creating Customer Segments/index.html
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Part 01-Module 09-Lesson 01_Predicting Boston Housing Prices/index.html
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Part 02-Module 08-Lesson 01_Machine Learning Capstone Project/index.html
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Part 01-Module 13-Lesson 01_PCA/28. PCA in sklearn-SBYdqlLgbGk.zh-CN.vtt
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Part 02-Module 04-Lesson 03_Policy-Based Methods/index.html
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Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/23. Error Function-V5kkHldUlVU.ja-JP.vtt
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/05. State-Value Functions-llakAjwox_8.en.vtt
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Part 02-Module 07-Lesson 01_Writing up a Capstone Proposal/index.html
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/15. Pooling Layers-OkkIZNs7Cyc.zh-CN.vtt
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Part 02-Module 04-Lesson 03_Policy-Based Methods/04. M2L3 04 V1-QicxmyE5vTo.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.ar.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/index.html
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Part 01-Module 01-Lesson 01_Welcome to Machine Learning/index.html
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/05. Interview with Art - Part 1-ClLYamtaO-Q.ar.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/10. TD Control Sarsamax-4DxoYuR7aZ4.en.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/05. Discretization-j2eZyUpy--E.en.vtt
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Part 02-Module 01-Lesson 01_Welcome to Advanced Machine Learning/index.html
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Part 01-Module 01-Lesson 02_What is Machine Learning/19. Kernel Method Answer-dRFd6HaAXys.zh-CN.vtt
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Part 02-Module 02-Lesson 02_Cloud Computing/index.html
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Part 01-Module 13-Lesson 01_PCA/17. Composite Features-spVqFnSvlIU.pt-BR.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/index.html
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Part 01-Module 01-Lesson 03_Introductory Practice Project/index.html
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/03. Elevator Pitch-S-nAHPrkQrQ.ja-JP.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.en.vtt
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Part 01-Module 15-Lesson 01_Random Projection and ICA/10. L6 6 ICA Applications MAIN V1 V1 V1-th12mTv1B7g.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/12. SVM 10 Polynomial Kernel 2 V2-9RfFvZ9DIRg.en.vtt
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Part 01-Module 10-Lesson 07_Supervised Learning Assessment/index.html
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Part 01-Module 07-Lesson 01_Model Selection/08. Grid Search SC V1-zDw-ZGiHW5I.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.en.vtt
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Part 02-Module 05-Lesson 01_Reinforcement Learning Assessment/index.html
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Part 01-Module 16-Lesson 01_Unsupervised Learning Assessment/index.html
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Part 02-Module 04-Lesson 02_Deep Q-Learning/04. Temporal Difference Learning-lpmDi0QeUm8.en.vtt
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Part 01-Module 04-Lesson 01_NumPy and pandas Assessment/index.html
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Part 02-Module 02-Lesson 06_Deep Learning Assessment/index.html
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Part 01-Module 14-Lesson 01_PCA Mini-Project/index.html
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Part 01-Module 18-Lesson 01_Congratulations!/index.html
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Part 03-Module 01-Lesson 01_Software and Tools/index.html
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Part 01-Module 15-Lesson 01_Random Projection and ICA/10. L6 6 ICA Applications MAIN V1 V1 V1-th12mTv1B7g.pt-BR.vtt
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Part 01-Module 07-Lesson 01_Model Selection/08. Grid Search SC V1-zDw-ZGiHW5I.en.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/11. 09 Quiz Fbeta Score SC V1-KSswld4_9bY.en.vtt
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Part 02-Module 04-Lesson 02_Deep Q-Learning/09. Deep Q-Learning Algorithm-MqTXoCxQ_eY.zh-CN.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/10. TD Control Sarsamax-4DxoYuR7aZ4.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-tfYAGBIR_Ws.ar.vtt
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/23. Visualizando CNNs-mnqS_EhEZVg.zh-CN.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/07. DL 08 AND And OR Perceptrons-Y-ImuxNpS40.en.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/09. Mean Absolute Error-vLKiY0Ehors.pt-BR.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/img/heaviside-step-function-2.gif
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/09. Perceptron Algorithm Pseudocode-p8Q3yu9YqYk.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/11. Perceptron Algorithm Pseudocode-p8Q3yu9YqYk.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/26. Conclusion-WhpE_8sTt-0.zh-CN.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/07. Goals and Rewards, Part 1-XPnj3Ya3EuM.en.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/02. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.pt-BR.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/02. Applications-CV6B84mKRNM.en.vtt
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Part 02-Module 04-Lesson 02_Deep Q-Learning/02. Neural Nets as Value Functions-cBi7vLrk8QQ.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/02. Unsupervised Learning-Mx9f99bRB3Q.en.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/10. SL NB 09 Bayesian Learning 3 V1 V4-u-Hj4RsJn1o.en.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/img/mse.png
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/01. Why Network-exjEm9Paszk.es-MX.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/01. Why Network-exjEm9Paszk.pt-BR.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/02. MLND SL EM 02 Bagging V1 MAIN V1-9L_B0Jcio3c.en.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.en.vtt
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Part 01-Module 13-Lesson 01_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.en.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/12. Kernel Functions-RdkPVYyVOvU.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/02. Unsupervised Learning-Mx9f99bRB3Q.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.ar.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/03. GitHub profile important items-prvPVTjVkwQ.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.pt-BR.vtt
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Part 01-Module 07-Lesson 01_Model Selection/02. Model Complexity Graph-Question-YS5OQCA5cLY.pt-BR.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/02. Introduction-tn-CrUTkCUc.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/11. Dropout RENDER-6DcImJS8uV8.ja-JP.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/15. SVM Answer-JrUtTwfnsfM.en.vtt
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Part 01-Module 13-Lesson 01_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.ar.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/09. 07 Recall SC V1-0n5wUZiefkQ.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Layers-pg99FkXYK0M.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/11. K-Means Clustering Visualization 2-fQXXa-CAoS0.zh-CN.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.pt-BR.vtt
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Part 01-Module 07-Lesson 01_Model Selection/02. Model Complexity Graph-Question-YS5OQCA5cLY.zh-CN.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/16. Compression While Preserving Information-NjuenhkC-44.pt-BR.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/06. SVM 05 Classification Error V1-nWGVAGXwvGE.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.ar.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. 29 Neural Network Architecture 2-FWN3Sw5fFoM.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/05. 09 Higher Dimensions-eBHunImDmWw.ja-JP.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/06. The Reward Hypothesis-uAqNwgZ49JE.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/14. 16 L Minimizing Cross-Entropy-YrDMXFhvh9E.en-US.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/02. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.zh-CN.vtt
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/06. Bellman Equations-UgIaDMvSdUo.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.ar.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/16. SVM 14 RBF Kernel 3 V1-DctkE8kaWPY.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/11. SVM 09 Polynomial Kernel 1 V1-8t2tVDHNBnk.en.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/02. Solving Problems - Big And Small-WHcRQMGSbqg.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/16. Compression While Preserving Information-NjuenhkC-44.en.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/03. MLND SL EM 03 AdaBoost V1 MAIN V1-HD6SRBWKGUE.en.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/04. MLND SL EM 04 Weighting The Data MAIN V1 V2-O-hh_x0iYW8.pt-BR.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.en.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/03. MLND SL EM 03 AdaBoost V1 MAIN V1-HD6SRBWKGUE.pt-BR.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.pt-BR.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/05. 09 Higher Dimensions-eBHunImDmWw.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/06. 09 Higher Dimensions-eBHunImDmWw.en.vtt
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Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.pt-BR.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/16. Higher Dimensions--UvpQV1qmiE.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/10. Entropy Formula-w73JTBVeyjE.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/03. GitHub profile important items-prvPVTjVkwQ.en.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/02. Applications-CV6B84mKRNM.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/06. SVM 05 Classification Error V1-nWGVAGXwvGE.zh-CN.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/17. Kernel Method Quiz-x0JqH6-Dhvw.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/13. Information Gain-k9iZL53PAmw.zh-CN.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/06. 04 Quiz False Negatives And Positives SC V1-_ytP9zIkziw.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/15. SVM Answer-JrUtTwfnsfM.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/15. SVM Answer-JrUtTwfnsfM.pt-BR.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/10. SL NB 09 Bayesian Learning 3 V1 V4-u-Hj4RsJn1o.zh-CN.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/09. Coarse Coding-Uu1J5KLAfTU.zh-CN.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/04. MLND SL EM 04 Weighting The Data MAIN V1 V2-O-hh_x0iYW8.en.vtt
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Part 01-Module 13-Lesson 01_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.ar.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/17. Kernel Method Quiz-x0JqH6-Dhvw.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-tfYAGBIR_Ws.en.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/04. SVM 03 Error Function V1-l-ahImxoi-U.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/03. Statistical Invariance-0Hr5YwUUhr0.ja-JP.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/02. Exemplo de classificação-Dh625piH7Z0.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/03. Exemplo de classificação-Dh625piH7Z0.en.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/22. 31 L Momentum And Learning Rate Decay-O3QYdmQjXds.ja-JP.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/21. Momentum-r-rYz_PEWC8.pt-BR.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/08. 06 Precision SC V1-q2wVorBfefU.en.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/06. TD Prediction Action Values-1c029-7_9GA.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/17. Other Activation Functions-kA-1vUt6cvQ.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.ja-JP.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/11. Dropout RENDER-6DcImJS8uV8.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/02. Unsupervised Learning-Mx9f99bRB3Q.zh-CN.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/06. 04 Quiz False Negatives And Positives SC V1-_ytP9zIkziw.pt-BR.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/15. Backpropagation-MZL97-2joxQ.ja-JP.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/17. Kernel Method Quiz-x0JqH6-Dhvw.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/04. Decision Trees Answer-h8zH47iFhCo.pt-BR.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/05. SL NB 04 Bayes Theorem V1 V2-nVbPJmf53AI.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/05. 09 Higher Dimensions-eBHunImDmWw.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/06. 09 Higher Dimensions-eBHunImDmWw.pt-BR.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/11. SVM 09 Polynomial Kernel 1 V1-8t2tVDHNBnk.pt-BR.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/15. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/03. GitHub profile important items-prvPVTjVkwQ.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/04. Decision Trees Answer-h8zH47iFhCo.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.en.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/08. 06 Precision SC V1-q2wVorBfefU.pt-BR.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. Perceptron Algorithm--zhTROHtscQ.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/10. Perceptron Algorithm--zhTROHtscQ.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/11. Dropout RENDER-6DcImJS8uV8.en-US.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/23. 32 L Parameter Hyperspace!-5a3-iIhdguc.ja-JP.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/08. Training Your Logistic Classifier-WQsdr1EJgz8.ja-JP.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/10. Entropy Formula-w73JTBVeyjE.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/07. Quick Fixes-Lb9e2KemR6I.ar.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/12. K-Means Clustering Visualization 3-WfwX3B4d8_I.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.zh-CN.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/04. Recommending Apps-nEvW8B1HNq4.zh-CN.vtt
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.ja-JP.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/04. Good GitHub repository-qBi8Q1EJdfQ.ar.vtt
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/04. Gridworld Example-XeHBmPFqTsE.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.ja-JP.vtt
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Part 01-Module 11-Lesson 01_Clustering/12. K-Means Clustering Visualization 3-WfwX3B4d8_I.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/17. Other Activation Functions-kA-1vUt6cvQ.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/10. Entropy Formula-w73JTBVeyjE.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/03. Clustering Movies-g8PKffm8IRY.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.ja-JP.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/02. Exemplo de classificação-Dh625piH7Z0.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/03. Exemplo de classificação-Dh625piH7Z0.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/23. 32 L Parameter Hyperspace!-5a3-iIhdguc.pt-BR.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/04. Recommending Apps-nEvW8B1HNq4.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/16. Compression While Preserving Information-NjuenhkC-44.zh-CN.vtt
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/04. Decision Trees Answer-h8zH47iFhCo.zh-CN.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/08. MLND SL EM 08 Combining The Models V1 MAIN V1-1GxscvKU2Ic.en.vtt
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Part 02-Module 04-Lesson 02_Deep Q-Learning/03. Monte Carlo Learning-qOviWYwcvsg.zh-CN.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/15. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.pt-BR.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/06. Student Admissions-TdgBi6LtOB8.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/15. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/21. Momentum-r-rYz_PEWC8.en.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.pt-BR.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/12. Kernel Functions-RdkPVYyVOvU.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/10. Mean Squared Error-MRyxmZDngI4.en.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/04. OpenAI Gym-MktEOWp3QLg.pt-BR.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/01. Introduction-bYeteZQrUcE.pt-BR.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/07. DL 08 AND And OR Perceptrons-Y-ImuxNpS40.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/08. DL 08 AND And OR Perceptrons-Y-ImuxNpS40.zh-CN.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/02. Solving Problems - Big And Small-WHcRQMGSbqg.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/10. SVM 08 The C Parameter V2-6CxPhVo0hRw.pt-BR.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/08. Training Your Logistic Classifier-WQsdr1EJgz8.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/10. SVM 08 The C Parameter V2-6CxPhVo0hRw.zh-CN.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Elevator Pitch-0QtgTG49E9I.ja-JP.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/01. Introduction-6jSFl5kxIBs.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/05. Training a Deep Learning Network-CsB7yUtMJyk.ja-JP.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.ja-JP.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/08. MLND SL EM 08 Combining The Models V1 MAIN V1-1GxscvKU2Ic.pt-BR.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.zh-CN.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/15. Backpropagation-MZL97-2joxQ.en-US.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. Perceptron Algorithm--zhTROHtscQ.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/10. Perceptron Algorithm--zhTROHtscQ.pt-BR.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/08. Training Your Logistic Classifier-WQsdr1EJgz8.pt-BR.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/01. Introduction-6jSFl5kxIBs.en.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/03. Statistical Invariance-0Hr5YwUUhr0.en.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/15. Backpropagation-MZL97-2joxQ.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/22. 31 L Momentum And Learning Rate Decay-O3QYdmQjXds.pt-BR.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/05. Resources-_YPqfAnCqtk.pt-BR.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/08. SL NB 07 Q Bayesian Learning 1 V1 V4-J4BmsKXPnkA.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/05. 09 Higher Dimensions-eBHunImDmWw.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/06. 09 Higher Dimensions-eBHunImDmWw.zh-CN.vtt
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Part 02-Module 03-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.pt-BR.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/04. SVM 03 Error Function V1-l-ahImxoi-U.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/02. Solving Problems - Big And Small-WHcRQMGSbqg.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/01. Introduction-bYeteZQrUcE.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/02. Exemplo de classificação-Dh625piH7Z0.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/03. Exemplo de classificação-Dh625piH7Z0.zh-CN.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.ja-JP.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/22. 31 L Momentum And Learning Rate Decay-O3QYdmQjXds.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. Perceptron Algorithm--zhTROHtscQ.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/10. Perceptron Algorithm--zhTROHtscQ.zh-CN.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/02. Logistic Regression - Question-kSs6O3R7JUI.ja-JP.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/17. Other Activation Functions-kA-1vUt6cvQ.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/06. Student Admissions-TdgBi6LtOB8.zh-CN.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/04. SVM 03 Error Function V1-l-ahImxoi-U.zh-CN.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/07. Summary-hvYQ_3LgCYs.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/11. Dropout RENDER-6DcImJS8uV8.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.pt-BR.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/05. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.ja-JP.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/06. Student Admissions-TdgBi6LtOB8.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-MEtIAGKweXU.ar.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/23. 32 L Parameter Hyperspace!-5a3-iIhdguc.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Multiclass Classification-uNTtvxwfox0.ja-JP.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/02. Logistic Regression - Question-kSs6O3R7JUI.en-US.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/11. Logistic Regression Question-wQXKdeVHTmc.en.vtt
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.en.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.en.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.pt-BR.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Elevator Pitch-0QtgTG49E9I.ar.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.ar.vtt
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Part 01-Module 11-Lesson 01_Clustering/12. K-Means Clustering Visualization 3-WfwX3B4d8_I.zh-CN.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/img/codecogseqn-2.png
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Part 01-Module 10-Lesson 01_Linear Regression/10. Mean Squared Error-MRyxmZDngI4.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.pt-BR.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/05. SL NB 04 Bayes Theorem V1 V2-nVbPJmf53AI.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-tfYAGBIR_Ws.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/03. Statistical Invariance-0Hr5YwUUhr0.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.en.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/02. Solving Problems - Big And Small-WHcRQMGSbqg.zh-CN.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/08. SL NB 07 Q Bayesian Learning 1 V1 V4-J4BmsKXPnkA.pt-BR.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/06. TD Prediction Action Values-1c029-7_9GA.zh-CN.vtt
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/21. Momentum-r-rYz_PEWC8.zh-CN.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/04. OpenAI Gym-MktEOWp3QLg.en.vtt
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/07. TD Control Sarsa(0)-LkFkjfsRpXc.en.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/08. SL NB 07 Q Bayesian Learning 1 V1 V4-J4BmsKXPnkA.zh-CN.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/04. Good GitHub repository-qBi8Q1EJdfQ.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.en.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/img/backprop-general.gif
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Part 01-Module 01-Lesson 02_What is Machine Learning/22. Hierarchical Clustering-1PldDT8AwMA.en.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.ar.vtt
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Part 01-Module 11-Lesson 01_Clustering/16. Counterintuitive Clusters-StmEUgT1XSY.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/23. What Is The Neural Network Looking At-qN-rvoxPbBw.en.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/23. 32 L Parameter Hyperspace!-5a3-iIhdguc.zh-CN.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/15. Backpropagation-MZL97-2joxQ.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/22. Hierarchical Clustering-1PldDT8AwMA.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.ar.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/05. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/08. Training Your Logistic Classifier-WQsdr1EJgz8.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Multiclass Classification-uNTtvxwfox0.pt-BR.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/03. Statistical Invariance-0Hr5YwUUhr0.zh-CN.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/01. Introduction-6jSFl5kxIBs.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/22. 31 L Momentum And Learning Rate Decay-O3QYdmQjXds.zh-CN.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/07. Summary-hvYQ_3LgCYs.zh-CN.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/03. Accuracy-s6SfhPTNOHA.en-US.vtt
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Part 02-Module 03-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Multiclass Classification-uNTtvxwfox0.en.vtt
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Part 02-Module 03-Lesson 01_Introduction to RL/05. Resources-_YPqfAnCqtk.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/img/codecogseqn-61.gif
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Part 01-Module 07-Lesson 01_Model Selection/04. KFold Cross Validation V3 V1-9W6o6eWGi-0.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-iCTPBcowJRY.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.en.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.ar.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Elevator Pitch-0QtgTG49E9I.en.vtt
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Part 02-Module 03-Lesson 03_The RL Framework The Solution/04. Gridworld Example-XeHBmPFqTsE.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/img/f1.gif
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Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.pt-BR.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/08. MLND - Unsupervised Learning - L3 08 Overview Of The Expectation Maximization Algorithm MAIN V1 V1-XdQfFnnj5Xo.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/05. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.en.vtt
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Part 01-Module 07-Lesson 01_Model Selection/04. KFold Cross Validation V3 V1-9W6o6eWGi-0.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.zh-CN.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/03. RL M2L4 03 Two Function Approximators V1-37KQEgLaLfw.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/04. Good GitHub repository-qBi8Q1EJdfQ.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.ja-JP.vtt
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Part 01-Module 11-Lesson 01_Clustering/16. Counterintuitive Clusters-StmEUgT1XSY.zh-CN.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/05. Training a Deep Learning Network-CsB7yUtMJyk.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/28. 1x1 Convolutions-Zmzgerm6SjA.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/07. Quick Fixes-Lb9e2KemR6I.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/28. 1x1 Convolutions-Zmzgerm6SjA.ja-JP.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/img/f2.gif
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Part 02-Module 03-Lesson 06_Temporal-Difference Methods/07. TD Control Sarsa(0)-LkFkjfsRpXc.zh-CN.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/14. Summary-MTEBk43oByU.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/23. Conclusion-hJEuaOUu2yA.pt-BR.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/03. Accuracy-s6SfhPTNOHA.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/07. Quick Fixes-Lb9e2KemR6I.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/01. What Is Deep Learning-INt1nULYPak.ja-JP.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/23. What Is The Neural Network Looking At-qN-rvoxPbBw.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-MEtIAGKweXU.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-HyjBus7S2gY.ar.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/02. 02 Skin Cancer V4-70jGZeiTNgk.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/11. Logistic Regression Question-wQXKdeVHTmc.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-MEtIAGKweXU.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/22. Visualization-aGIGB4Ta3_A.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/09. Regularization-QcJBhbuCl5g.ja-JP.vtt
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/23. Conclusion-hJEuaOUu2yA.en.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/02. Logistic Regression - Question-kSs6O3R7JUI.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/04. Multiclass Classification-uNTtvxwfox0.zh-CN.vtt
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Part 02-Module 03-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.ar.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/05. MLND SL DT 04 Q Student Admissions V3 MAIN V1-MOa335cQGI4.en.vtt
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Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.zh-CN.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/13. Non-Linear Function Approximation-rITnmpD2mN8.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.ja-JP.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/08. Entropy Formula-iZiSYrOKvpo.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/03. 分类问题 2 -46PywnGa_cQ.ja-JP.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/22. Visualization-aGIGB4Ta3_A.pt-BR.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/05. Naive Bayes Quiz-jsLkVYXmr3E.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/08. Entropy Formula-iZiSYrOKvpo.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/29. Inception Module-SlTm03bEOxA.ja-JP.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/12. Non-Linear Regions-B8UrWnHh1Wc.en.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/16. MLND - Unsupervised Learning - L3 17 Cluster Validation MAINv1 V1-N13ML_GUuZQ.zh-CN.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/03. 分类问题 2 -46PywnGa_cQ.en.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/08. MLND - Unsupervised Learning - L3 08 Overview Of The Expectation Maximization Algorithm MAIN V1 V1-XdQfFnnj5Xo.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/04. 分类问题 2 -46PywnGa_cQ.en.vtt
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Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.en.vtt
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Part 02-Module 03-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.ar.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/img/hidden-layer-weights.gif
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/05. Naive Bayes Quiz-jsLkVYXmr3E.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/23. Conclusion-hJEuaOUu2yA.zh-CN.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/12. MLND SL NB Solution Naive Bayes Algorithm-QDj3xzjuYmo.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/02. 02 Skin Cancer V4-70jGZeiTNgk.pt-BR.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/06. Chain Rule-YAhIBOnbt54.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.ar.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.ar.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/05. The Data-2RLbbV7MQNA.zh-CN.vtt
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Part 01-Module 07-Lesson 01_Model Selection/12. Outro SC V1-YD1grQje9fw.en.vtt
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Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.zh-CN.vtt
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Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.ar.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/03. Accuracy-s6SfhPTNOHA.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.zh-CN.vtt
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Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.pt-BR.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/14. Summary-MTEBk43oByU.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-ncFtwW5urHk.ja-JP.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/08. Gradient Descent-BEC0uH1fuGU.en.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/10. Gradient Descent-29PmNG7fuuM.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/03. 分类问题 2 -46PywnGa_cQ.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/04. 分类问题 2 -46PywnGa_cQ.pt-BR.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/img/f6.gif
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.pt-BR.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/05. MLND SL DT 04 Q Student Admissions V3 MAIN V1-MOa335cQGI4.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/03. Let'S Get Started-ySIDqaXLhHw.ja-JP.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/09. SL NB 08 S Bayesian Learning 2 V1 V6-3rIYZgCXVXY.pt-BR.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/09. SL NB 08 S Bayesian Learning 2 V1 V6-3rIYZgCXVXY.en.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/01. What Is Deep Learning-INt1nULYPak.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/29. Inception Module-SlTm03bEOxA.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.en.vtt
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Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-gg7SAMMl4kM.ar.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/29. Inception Module-SlTm03bEOxA.pt-BR.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/03. MLND SL DT 02 Recommending Apps 2 MAIN V3-KSrIYqKZwCA.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/12. Non-Linear Regions-B8UrWnHh1Wc.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/16. Vanishing Gradient-W_JJm_5syFw.pt-BR.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/13. Non-Linear Function Approximation-rITnmpD2mN8.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/07. Naive Bayes Answer-YKN-fjuZ1VU.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-iCTPBcowJRY.en.vtt
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Part 01-Module 13-Lesson 01_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/01. Mat HS-9P7UPWFu8w8.en-US.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/25. Confusion Matrix-3rpN-YYlfes.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-HyjBus7S2gY.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.pt-BR.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.en.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/02. MLND SL DT 01 Recommending Apps 1 MAIN V3-uI_yNrqqKVg.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/08. Gradient Descent-BEC0uH1fuGU.pt-BR.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/10. Gradient Descent-29PmNG7fuuM.pt-BR.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.ja-JP.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/12. Non-Linear Regions-B8UrWnHh1Wc.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.ar.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/09. Regularization-QcJBhbuCl5g.pt-BR.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/12. MLND SL NB Solution Naive Bayes Algorithm-QDj3xzjuYmo.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en-US.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/09. Linear Regression Question-sf51L0RN6zc.en.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/09. Linear Regression Question-sf51L0RN6zc.pt-BR.vtt
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Part 02-Module 04-Lesson 02_Deep Q-Learning/13. Wrap Up-x6JggcDTcys.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.pt-BR.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/28. 1x1 Convolutions-Zmzgerm6SjA.zh-CN.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/22. Visualization-aGIGB4Ta3_A.zh-CN.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/20. Recap and Challenge-ecREasTrKu4.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-HyjBus7S2gY.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.ja-JP.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/09. Linear Regression Question-sf51L0RN6zc.zh-CN.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-ncFtwW5urHk.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/17. 16 Solution Diagnosing Cancer V3-IJYvt2ssUFk.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/09. Regularization-QcJBhbuCl5g.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/20. Recap and Challenge-ecREasTrKu4.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/15. Participating in open source projects 2-elZCLxVvJrY.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/16. Vanishing Gradient-W_JJm_5syFw.en.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.pt-BR.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/03. MLND SL DT 02 Recommending Apps 2 MAIN V3-KSrIYqKZwCA.pt-BR.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/03. RL M2L4 03 Two Function Approximators V1-37KQEgLaLfw.zh-CN.vtt
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Part 01-Module 05-Lesson 01_Training and Testing Models/02. 02 Intro SC V1-mIgABrjJVBY.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.en-US.vtt
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Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-iCTPBcowJRY.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/12. Dropout Pt. 2-8nG8zzJMbZw.ja-JP.vtt
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Part 02-Module 04-Lesson 02_Deep Q-Learning/01. Intro to Deep Q-Learning-o3cmuUDhP3I.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.en.vtt
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Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-MEtIAGKweXU.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/08. MLND - Unsupervised Learning - L3 08 Overview Of The Expectation Maximization Algorithm MAIN V1 V1-XdQfFnnj5Xo.zh-CN.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.es-MX.vtt
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Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/01. What Is Deep Learning-INt1nULYPak.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/29. Inception Module-SlTm03bEOxA.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/04. Fitting A Line-gkdoknEEcaI.pt-BR.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/06. MLND - Unsupervised Learning - L3 06 GMM In 2D MAIN Sfx V1 V1-GsNWVHmRRG4.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/06. Chain Rule-YAhIBOnbt54.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/04. Fitting A Line-gkdoknEEcaI.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/25. Confusion Matrix-3rpN-YYlfes.zh-CN.vtt
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Part 01-Module 10-Lesson 03_Decision Trees/03. MLND SL DT 02 Recommending Apps 2 MAIN V3-KSrIYqKZwCA.zh-CN.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/10. Gradient Descent-29PmNG7fuuM.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/img/y.gif
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Part 01-Module 01-Lesson 02_What is Machine Learning/08. Gradient Descent-BEC0uH1fuGU.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/03. Non-Linear Models-HWuBKCZsCo8.ja-JP.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/01. Mat HS-9P7UPWFu8w8.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/03. SVM 02 Minimizing Distances V1-mNKk2dBsNGA.en.vtt
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Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.pt-BR.vtt
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Part 01-Module 05-Lesson 01_Training and Testing Models/02. 02 Intro SC V1-mIgABrjJVBY.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-ncFtwW5urHk.en.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/14. Multilayer perceptrons-Rs9petvTBLk.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/03. Non-Linear Models-HWuBKCZsCo8.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/09. 为何是神经网络-zAkzOZntK6Y.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/20. Recap and Challenge-ecREasTrKu4.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-HyjBus7S2gY.zh-CN.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/14. Summary-MTEBk43oByU.zh-CN.vtt
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Part 01-Module 10-Lesson 08_Supervised Learning Project/01. ML Charity Project-aVodYHcOB8U.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/04. Medical Classification-RCOSP60dV7U.en.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.en.vtt
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Part 02-Module 04-Lesson 04_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.zh-CN.vtt
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Part 02-Module 04-Lesson 03_Policy-Based Methods/08. M2L3 08 V1-og3W6CXn1F0.en.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/01. What Is Deep Learning-INt1nULYPak.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/03. Let'S Get Started-ySIDqaXLhHw.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/16. Counterintuitive Clusters-aveIz1JYeAg.ar.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/09. SL NB 08 S Bayesian Learning 2 V1 V6-3rIYZgCXVXY.zh-CN.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/17. 16 Solution Diagnosing Cancer V3-IJYvt2ssUFk.pt-BR.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/02. Continuous Perceptrons-07-JJ-aGEfM.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/02. Continuous Perceptrons-07-JJ-aGEfM.ja-JP.vtt
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Part 01-Module 10-Lesson 08_Supervised Learning Project/01. ML Charity Project-aVodYHcOB8U.en.vtt
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Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.ar.vtt
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Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-iCTPBcowJRY.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-xJtmPbEfpFo.ar.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-4Fkfu37el_k.ar.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/img/codecogseqn-62.gif
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Part 02-Module 02-Lesson 03_Deep Neural Networks/02. Continuous Perceptrons-07-JJ-aGEfM.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-ncFtwW5urHk.zh-CN.vtt
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Part 01-Module 15-Lesson 01_Random Projection and ICA/03. L6 2 Random Projection Impl MAINv1 V1 V1-5DhvurLgRII.pt-BR.vtt
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Part 02-Module 04-Lesson 01_RL in Continuous Spaces/13. Non-Linear Function Approximation-rITnmpD2mN8.zh-CN.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.pt-BR.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/03. Non-Linear Models-HWuBKCZsCo8.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/15. Participating in open source projects 2-elZCLxVvJrY.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/21. Polynomial Regression-DBhWG-PagEQ.en.vtt
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Part 01-Module 13-Lesson 01_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-5j6VZr8sHo8.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-gg7SAMMl4kM.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/07. Supervised Classification-XTGsutypAPE.ja-JP.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/09. Regularization-QcJBhbuCl5g.zh-CN.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/02. MLND - Unsupervised Learning - L3 2 Gaussian Mixture Model Clustering MAIN V1 V2-Y_methsXoFA.pt-BR.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/15. SVM 13 RBF Kernel 2 V1-ozl9UWVP0MI.en.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/09. 为何是神经网络-zAkzOZntK6Y.pt-BR.vtt
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Part 02-Module 04-Lesson 02_Deep Q-Learning/01. Intro to Deep Q-Learning-o3cmuUDhP3I.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/03. Let'S Get Started-ySIDqaXLhHw.en.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/05. MLND SL EM 05 Weighting The Models MAIN V1-wn6K536dPLc.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/19. Learning Rate-TwJ8aSZoh2U.pt-BR.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.zh-CN.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/17. 16 Solution Diagnosing Cancer V3-IJYvt2ssUFk.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.en.vtt
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Part 02-Module 04-Lesson 03_Policy-Based Methods/08. M2L3 08 V1-og3W6CXn1F0.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/16. Vanishing Gradient-W_JJm_5syFw.zh-CN.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/03. SL NB 02 Known And Inferred V1 V2-DrYfZXiDLQI.en.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.ar.vtt
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Part 01-Module 05-Lesson 01_Training and Testing Models/08. MLND Turning Paramaters-eSv2lPcnRM0.pt-BR.vtt
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Part 02-Module 03-Lesson 02_The RL Framework The Problem/01. Introduction-X_9l_ZqXXBA.zh-CN.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/01. Naive Bayes Intro V2-vNOiQXghgRY.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/16. 17 L Transition Into Practical Aspects Of Learning-bKqkRFOOKoA.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-ZwMY5rAAd7Q.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.en.vtt
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Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-PRjmvj6Vubs.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.ja-JP.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.ar.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.ar.vtt
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/01. Apresentando Alexis-38ExGpdyvJI.en.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/01. Naive Bayes Intro V2-vNOiQXghgRY.pt-BR.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/04. Accuracy 2-ueYCLfd_aNQ.en.vtt
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Part 01-Module 13-Lesson 01_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.pt-BR.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/02. Color-Question-BdQccpMwk80.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.ar.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.ja-JP.vtt
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-lS5DfbsWH34.zh-CN.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/12. Reflect on your commit messages-_0AHmKkfjTo.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-xSQTzAeeoEc.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.pt-BR.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/17. Numerical Stability-_SbGcOS-jcQ.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-xSQTzAeeoEc.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.ja-JP.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/12. 13 L One Hot Encoding-phYsxqlilUk.pt-BR.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/04. Accuracy 2-ueYCLfd_aNQ.pt.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.pt-BR.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/29. Conclusion-wOiUQDgGD9E.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/20. Solution ROC Curve-sdUUf6RRmXI.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.pt-BR.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.pt-BR.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.en-US.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-ZwMY5rAAd7Q.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-xSQTzAeeoEc.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.en.vtt
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Part 01-Module 10-Lesson 04_Naive Bayes/01. Naive Bayes Intro V2-vNOiQXghgRY.zh-CN.vtt
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Part 03-Module 02-Lesson 01_Intro to TensorFlow/12. 13 L One Hot Encoding-phYsxqlilUk.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.ar.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.en.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/04. Accuracy 2-ueYCLfd_aNQ.pt-BR.vtt
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/01. Apresentando Alexis-38ExGpdyvJI.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/02. Color-Question-BdQccpMwk80.zh-CN.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/12. Reflect on your commit messages-_0AHmKkfjTo.ja-JP.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.ar.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/01. Introducing Luis-nto-stLuN6M.en-US.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/13. SVM Question-Fwnjx0s_AIw.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/14. Some challenges of k-means-e2CdlG5P4WA.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.pt-BR.vtt
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Part 02-Module 02-Lesson 04_Convolutional Neural Networks/01. Apresentando Alexis-38ExGpdyvJI.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/13. Participating in open source projects-OxL-gMTizUA.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/17. Composite Features-0ZBp8oWySAc.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.en.vtt
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Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.zh-CN.vtt
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Part 03-Module 03-Lesson 01_Intro to Neural Networks/01. Introducing Luis-nto-stLuN6M.pt-BR.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/13. SVM Question-Fwnjx0s_AIw.zh-CN.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/23. Conclusion-pyeojf0NniQ.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/05. Match Points with Clusters-wJV1cRjmIYY.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.zh-CN.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/26. Keras Lab-a50un22BsLI.en.vtt
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Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.en.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/26. Keras Lab-a50un22BsLI.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.en.vtt
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Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.ar.vtt
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.ar.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.ar.vtt
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Part 01-Module 10-Lesson 01_Linear Regression/23. Conclusion-pyeojf0NniQ.en.vtt
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Part 03-Module 04-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.zh-CN.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-ZwMY5rAAd7Q.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.zh-CN.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.en.vtt
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Part 01-Module 13-Lesson 01_PCA/17. Composite Features-0ZBp8oWySAc.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/01. Support Vector Machine V2-LBmM6pZCrI0.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-U3FUxkm1MxI.ar.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/11. Supervised Learning Outro V2-7X2SDqzGrdU.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/14. Some challenges of k-means-e2CdlG5P4WA.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/12. Reflect on your commit messages-_0AHmKkfjTo.pt-BR.vtt
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Part 01-Module 07-Lesson 01_Model Selection/13. MLND Outro-sFvMBncQjr8.pt-BR.vtt
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Part 01-Module 06-Lesson 01_Evaluation Metrics/04. Accuracy 2-ueYCLfd_aNQ.zh-CN.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.ar.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.pt-BR.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/09. SVM 07 Error Function V1-A1wbrcSYc1c.en.vtt
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Part 01-Module 07-Lesson 01_Model Selection/13. MLND Outro-sFvMBncQjr8.en.vtt
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Part 01-Module 01-Lesson 02_What is Machine Learning/13. SVM Question-Fwnjx0s_AIw.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.ar.vtt
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Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-9J3IwQFXveI.ar.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.en.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/12. Reflect on your commit messages-_0AHmKkfjTo.en.vtt
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Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/17. Composite Features-0ZBp8oWySAc.zh-CN.vtt
498 Bytes
Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-U3FUxkm1MxI.ja-JP.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-FpQm_dYA9LM.ar.vtt
490 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.ar.vtt
490 Bytes
Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.en.vtt
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Part 01-Module 10-Lesson 06_Ensemble Methods/11. Supervised Learning Outro V2-7X2SDqzGrdU.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/06. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.zh-CN.vtt
488 Bytes
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.zh-CN.vtt
487 Bytes
Part 01-Module 13-Lesson 01_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.zh-CN.vtt
485 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.ja-JP.vtt
484 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.pt-BR.vtt
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Part 02-Module 02-Lesson 01_Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-FY0DXe0lfrI.ar.vtt
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Part 02-Module 02-Lesson 03_Deep Neural Networks/20. Random Restart-idyBBCzXiqg.pt-BR.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. DL 10 S Perceptron Algorithm-fATmrG2hQzI.ja-JP.vtt
477 Bytes
Part 02-Module 02-Lesson 01_Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.ja-JP.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/13. Participating in open source projects-OxL-gMTizUA.en.vtt
476 Bytes
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.zh-CN.vtt
475 Bytes
Part 01-Module 13-Lesson 01_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.pt-BR.vtt
474 Bytes
Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.ja-JP.vtt
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473 Bytes
Part 01-Module 13-Lesson 01_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.en.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.zh-CN.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/09. SVM 07 Error Function V1-A1wbrcSYc1c.zh-CN.vtt
467 Bytes
Part 02-Module 02-Lesson 03_Deep Neural Networks/20. Random Restart-idyBBCzXiqg.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/09. SVM 07 Error Function V1-A1wbrcSYc1c.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-U3FUxkm1MxI.pt-BR.vtt
460 Bytes
Part 01-Module 11-Lesson 01_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.en.vtt
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Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.en.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.pt-BR.vtt
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Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.zh-CN.vtt
456 Bytes
Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.pt-BR.vtt
454 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.en.vtt
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Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-uC1Xwc7warg.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.zh-CN.vtt
440 Bytes
Part 01-Module 11-Lesson 01_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.pt-BR.vtt
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Part 01-Module 07-Lesson 01_Model Selection/13. MLND Outro-sFvMBncQjr8.zh-CN.vtt
437 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.en.vtt
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Part 01-Module 10-Lesson 05_Support Vector Machines/01. Support Vector Machine V2-LBmM6pZCrI0.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.ar.vtt
425 Bytes
Part 01-Module 11-Lesson 01_Clustering/10. K-Means Cluster Visualization-ZMfwPUrOFsE.zh-CN.vtt
424 Bytes
Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.pt-BR.vtt
423 Bytes
Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.zh-CN.vtt
422 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.pt-BR.vtt
421 Bytes
Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt
420 Bytes
Part 02-Module 02-Lesson 01_Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt
420 Bytes
Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.pt-BR.vtt
420 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.en.vtt
419 Bytes
Part 02-Module 02-Lesson 03_Deep Neural Networks/20. Random Restart-idyBBCzXiqg.zh-CN.vtt
419 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-U3FUxkm1MxI.en.vtt
419 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.en.vtt
418 Bytes
Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.pt-BR.vtt
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Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-FpQm_dYA9LM.en.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-FpQm_dYA9LM.pt-BR.vtt
402 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.en.vtt
399 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.zh-CN.vtt
396 Bytes
Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.en.vtt
395 Bytes
Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.ar.vtt
393 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-U3FUxkm1MxI.zh-CN.vtt
392 Bytes
Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. DL 10 S Perceptron Algorithm-fATmrG2hQzI.zh-CN.vtt
390 Bytes
Part 02-Module 02-Lesson 01_Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.zh-CN.vtt
390 Bytes
Part 03-Module 05-Lesson 01_Convolutional Neural Networks/01. Intro to CNNs-B61jxZ4rkMs.ja-JP.vtt
386 Bytes
Part 01-Module 11-Lesson 01_Clustering/04. How Many Clusters-8Ygq5dRV0Kk.zh-CN.vtt
385 Bytes
Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-nvLhUSSUhiY.ar.vtt
385 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.en.vtt
371 Bytes
Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-FY0DXe0lfrI.pt-BR.vtt
370 Bytes
Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-9J3IwQFXveI.pt-BR.vtt
369 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.zh-CN.vtt
369 Bytes
Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-FY0DXe0lfrI.en.vtt
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Part 01-Module 10-Lesson 02_Perceptron Algorithm/08. DL 10 S Perceptron Algorithm-fATmrG2hQzI.pt-BR.vtt
364 Bytes
Part 02-Module 02-Lesson 01_Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.pt-BR.vtt
364 Bytes
Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.pt-BR.vtt
362 Bytes
Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-FY0DXe0lfrI.zh-CN.vtt
361 Bytes
Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.zh-CN.vtt
361 Bytes
Part 01-Module 13-Lesson 01_PCA/03. One-Dimensional, or Two-QsncWsyboFk.ar.vtt
360 Bytes
Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.ar.vtt
359 Bytes
Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-bAZJT4xHiXM.ar.vtt
357 Bytes
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.zh-CN.vtt
357 Bytes
Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-9J3IwQFXveI.en.vtt
355 Bytes
Part 01-Module 11-Lesson 01_Clustering/08. Match Points (again)-9J3IwQFXveI.zh-CN.vtt
355 Bytes
Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.zh-CN.vtt
342 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.zh-CN.vtt
335 Bytes
Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-uC1Xwc7warg.zh-CN.vtt
332 Bytes
Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.pt-BR.vtt
331 Bytes
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Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-uC1Xwc7warg.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.pt-BR.vtt
326 Bytes
Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.en.vtt
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Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/01. Intro to CNNs-B61jxZ4rkMs.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.en.vtt
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Part 01-Module 13-Lesson 01_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.zh-CN.vtt
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Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-nvLhUSSUhiY.en.vtt
315 Bytes
Part 01-Module 11-Lesson 01_Clustering/07. Moving Centers 2-uC1Xwc7warg.en.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/01. Intro to CNNs-B61jxZ4rkMs.en-US.vtt
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Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-nvLhUSSUhiY.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.zh-CN.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/01. Intro to CNNs-B61jxZ4rkMs.en.vtt
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Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-bAZJT4xHiXM.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.ar.vtt
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Part 03-Module 05-Lesson 01_Convolutional Neural Networks/01. Intro to CNNs-B61jxZ4rkMs.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-FpQm_dYA9LM.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.en.vtt
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Part 01-Module 13-Lesson 01_PCA/03. One-Dimensional, or Two-QsncWsyboFk.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.ar.vtt
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Part 01-Module 11-Lesson 01_Clustering/15. Limitations of K-Means-nvLhUSSUhiY.zh-CN.vtt
277 Bytes
Part 01-Module 13-Lesson 01_PCA/03. One-Dimensional, or Two-QsncWsyboFk.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-bAZJT4xHiXM.en.vtt
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Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.pt-BR.vtt
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Part 01-Module 11-Lesson 01_Clustering/09. Handoff to Katie-knrPsGtpyQY.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/01. Data Dimensionality-bAZJT4xHiXM.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.pt-BR.vtt
226 Bytes
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208 Bytes
Part 01-Module 11-Lesson 01_Clustering/09. Handoff to Katie-knrPsGtpyQY.en.vtt
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180 Bytes
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Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.pt-BR.vtt
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Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.en.vtt
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0. Websites you may like/3. (NulledPremium.com) Download Cracked Website Themes, Plugins, Scripts And Stock Images.url
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Part 01-Module 12-Lesson 01_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.en.vtt
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Part 01-Module 13-Lesson 01_PCA/11. Practice Finding New Axes-th34aboBOO0.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/11. Practice Finding New Axes-th34aboBOO0.en.vtt
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Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.zh-CN.vtt
125 Bytes
Part 01-Module 12-Lesson 01_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.pt-BR.vtt
124 Bytes
Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-FZVBF1HR4U0.ar.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.ar.vtt
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Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-FZVBF1HR4U0.zh-CN.vtt
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Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-FZVBF1HR4U0.en.vtt
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Part 01-Module 13-Lesson 01_PCA/10. Practice Finding Centers-FZVBF1HR4U0.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.en.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.zh-CN.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.pt-BR.vtt
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Part 01-Module 12-Lesson 01_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.en.vtt
104 Bytes
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