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- GetFreeCourses.Co-Udemy-CNN for Computer Vision with Keras and TensorFlow in Python.zip 2.6 GB
- 1. Cold Iron Light.flac 51.4 MB
- 8. Keras.flac 44.7 MB
- 7. Low Winter Sun.flac 42.9 MB
- 6. October Dawn.flac 40.6 MB
- 3. Black Square Icon.flac 38.1 MB
- 4. The Wood Demon.flac 36.0 MB
- 2. Temple of Zaum.flac 30.0 MB
- 5. Move 37.flac 27.8 MB
- Cracked Machine - Gates of Keras (2020) [FLAC].cuetools.flac.cue 652 Bytes
- 2. Working with the Keras Functional API/CNNs and Basic Image Classification - Mastering Keras [Video].mp4 252.4 MB
- 3. Developing and Implementing Deep Generative Models/Implementing VAEs in Keras - Mastering Keras [Video].mp4 65.5 MB
- 7. One-Shot and Deep Semi-Supervised Learning/Siamese Networks - Mastering Keras [Video].mp4 56.5 MB
- 3. Developing and Implementing Deep Generative Models/Implementing GANs in Keras - Mastering Keras [Video].mp4 54.5 MB
- 2. Working with the Keras Functional API/MLPs and Simple Data Analytics - Mastering Keras [Video].mp4 54.0 MB
- 2. Working with the Keras Functional API/RNNs and Sequential Data Analysis - Mastering Keras [Video].mp4 52.6 MB
- 6. Deep Reinforcement Learning/(Epsilon) Q-Learning and Deep Q-Networks - Mastering Keras [Video].mp4 51.5 MB
- 6. Deep Reinforcement Learning/Dealing with Instability (1)- Experiential Replay - Mastering Keras [Video].mp4 45.1 MB
- 6. Deep Reinforcement Learning/Advantage Networks - Mastering Keras [Video].mp4 42.4 MB
- 4. Advanced CNNs/Residual Networks-Layers - Mastering Keras [Video].mp4 40.1 MB
- 4. Advanced CNNs/Working with Inception Networks- Layers - Mastering Keras [Video].mp4 35.1 MB
- 2. Working with the Keras Functional API/AEs and Denoising Data - Mastering Keras [Video].mp4 30.5 MB
- 6. Deep Reinforcement Learning/Dealing with Instability (2)- Double Deep Q-Networks - Mastering Keras [Video].mp4 27.8 MB
- 4. Advanced CNNs/Dense Networks - Mastering Keras [Video].mp4 27.7 MB
- 4. Advanced CNNs/Transfer Learning- Applying Advanced Architectures on Real Data - Mastering Keras [Video].mp4 25.4 MB
- 5. Object Detection/Fast RCNNs - Mastering Keras [Video].mp4 22.8 MB
- 5. Object Detection/Region Proposal Networks and Faster RCNNs - Mastering Keras [Video].mp4 22.7 MB
- 1. Preparing Yourself for Mastering Keras Journey/Setting Up the Environment and Teaching Methodology.mp4 21.1 MB
- 6. Deep Reinforcement Learning/Reinforcement Learning Basics - Mastering Keras [Video].mp4 20.5 MB
- 7. One-Shot and Deep Semi-Supervised Learning/Semi-Supervised Learning Using GANs - Mastering Keras [Video].mp4 20.1 MB
- 01-welcome-to-the-course/004-installation-video-guide.mp4 47.4 MB
- 03-machine-learning/045-exercise-2-solution.mp4 45.3 MB
- 03-machine-learning/031-linear-regression-code-along.mp4 41.8 MB
- 03-machine-learning/043-exercise-1-solution.mp4 39.1 MB
- 04-deep-learning-intro/051-multiclass-classification-code-along.mp4 35.6 MB
- 05-gradient-descent/070-learning-rate-code-along.mp4 34.8 MB
- 01-welcome-to-the-course/007-your-first-deep-learning-model.mp4 34.5 MB
- 02-data/011-plotting-with-matplotlib.mp4 34.4 MB
- 05-gradient-descent/077-inner-layers-visualization-code-along.mp4 33.8 MB
- 02-data/009-data-exploration-with-pandas-code-along.mp4 32.4 MB
- 09-improving-performance/131-movies-reviews-sentiment-analysis-code-along.mp4 28.0 MB
- 04-deep-learning-intro/057-exercise-2-solution.mp4 26.4 MB
- 04-deep-learning-intro/055-exercise-1-solution.mp4 26.0 MB
- 01-welcome-to-the-course/002-real-world-applications-of-deep-learning.mp4 24.7 MB
- 03-machine-learning/035-classification-code-along.mp4 24.0 MB
- 08-recurrent-neural-networks/116-rolling-windows-code-along.mp4 22.1 MB
- 04-deep-learning-intro/049-neural-networks-code-along.mp4 22.1 MB
- 04-deep-learning-intro/059-exercise-3-solution.mp4 21.6 MB
- 06-convolutional-neural-networks/089-mnist-classification-code-along.mp4 20.6 MB
- 05-gradient-descent/068-numpy-arrays-code-along.mp4 20.4 MB
- [ FreeCourseWeb.com ] Egghead - Fully Connected Neural Networks with Keras.zip 120.8 MB
- [ FreeCourseWeb.com ] Packt - Deep Learning and Neural Networks using Python - Keras- The Complete Beginners Guide.zip 3.9 GB
- 4. Image Processing & Model Training/7. Training a Model.mp4 114.7 MB
- 5. Convolution & Pooling/3. Diagramming Convolutions & Pooling.mp4 112.7 MB
- 5. Convolution & Pooling/6. Neural Network Attention.mp4 112.4 MB
- 6. Text Analytics/2. Natural Language Processing.mp4 97.5 MB
- 3. Linear Regression/8. Learning Rate & Gradients.mp4 91.5 MB
- 6. Text Analytics/5. Reinforcement Learning.mp4 85.5 MB
- 6. Text Analytics/4. Long Short Term Memory.mp4 84.9 MB
- 4. Image Processing & Model Training/8. Comparing Different Models.mp4 80.8 MB
- 3. Linear Regression/3. Tensorflow Architecture.mp4 79.7 MB
- 6. Text Analytics/1. Detecting Good & Bad Reviews.mp4 78.8 MB
- 5. Convolution & Pooling/4. Visualizing Convolutional Operations.mp4 78.8 MB
- 5. Convolution & Pooling/5. Predicting, Saving & Loading Models.mp4 71.3 MB
- 4. Image Processing & Model Training/6. Defining the Solver & Loss Function.mp4 70.9 MB
- 6. Text Analytics/3. Sentiment Analysis.mp4 69.4 MB
- 3. Linear Regression/9. Learning Rate vs Steps.mp4 67.8 MB
- 4. Image Processing & Model Training/9. Principal Component Analysis.mp4 64.6 MB
- 2. Machine Learning, Neural Networks & Deep Learning/1. Machine Learning Demo.mp4 61.2 MB
- 4. Image Processing & Model Training/1. Image Processing with Keras.mp4 60.0 MB
- 3. Linear Regression/5. Plotting Data with Noise.mp4 59.7 MB
- 4. Image Processing & Model Training/5. Understanding the Model.mp4 57.2 MB
- [ FreeCourseWeb.com ] Packt - Keras Tips, Tricks, and Techniques.zip 2.8 GB
- [ FreeCourseWeb.com ] Udemy - CNN for Computer Vision with Keras and TensorFlow in R.zip 2.8 GB
- [ FreeCourseWeb.com ] Udemy - Deep Learning for Computer Vision with Tensor Flow and Keras.zip 5.4 GB
- [ FreeCourseWeb.com ] PluralSight - Building Image Classification Solutions Using Keras and Transfer Learning.zip 663.8 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (28).mp4 196.5 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (27).mp4 188.6 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (2).mp4 188.1 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (20).mp4 185.1 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (25).mp4 179.8 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (3).mp4 179.5 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (22).mp4 177.9 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (26).mp4 177.8 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (21).mp4 176.5 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (7).mp4 176.3 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (16).mp4 173.7 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (18).mp4 173.7 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (5).mp4 171.0 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (1).mp4 170.6 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (10).mp4 167.2 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (11).mp4 165.6 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (9).mp4 164.8 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (6).mp4 161.7 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (15).mp4 147.8 MB
- A Practical Guide to Deep Learning with TensorFlow 2.0 and K (17).mp4 140.9 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
- 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
- 7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
- 7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
- 4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/15. R - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 226.6 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/12. Python - Regression problems and Functional API/1. Building Neural Network for Regression Problem.mp4 163.4 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/14. Python - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 159.0 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/13. R - Regression Problem and Functional API/1. Building Regression Model with Functional AP.mp4 137.5 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/11. R - Building and training the Model/1. Building,Compiling and Training.mp4 137.1 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/5. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 128.1 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/9. Dataset for classification problem/3. R - Dataset, Normalization and Test-Train set.mp4 117.2 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/18. Add on Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4 105.4 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/11. R - Building and training the Model/2. Evaluating and Predicting.mp4 104.1 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/18. Add on Data Preprocessing/8. EDD in R.mp4 101.7 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/3. Setting up R Studio and R Crash Course/7. Creating Barplots in R.mp4 101.5 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/12. Python - Regression problems and Functional API/2. Using Functional API for complex architectures.mp4 96.6 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/4. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 90.8 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/3. Setting up R Studio and R Crash Course/3. Packages in R.mp4 87.0 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 85.6 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/13. R - Regression Problem and Functional API/2. Complex Architectures using Functional API.mp4 83.4 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 83.0 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/19. Test Train Split/4. Test train split in R.mp4 79.3 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/18. Add on Data Preprocessing/10. Outlier Treatment in Python.mp4 73.7 MB
- [TutsNode.com] - Artificial Neural Networks (ANN) with Keras in Python and R/10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 73.3 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
- 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
- 7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
- 7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
- 4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
- [ FreeCourseWeb.com ] Probabilistic Deep Learning With Python, Keras and TensorFlow Probability [Final Version].zip 57.4 MB
- 1. Course Overview, Installs, and Setup/2. Course Setup and Installation.mp4 159.8 MB
- 13. Deployment/7. Flask Front End.mp4 156.9 MB
- 9. Recurrent Neural Networks - RNNs/14. Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
- 9. Recurrent Neural Networks - RNNs/13. RNN Exercise - Solutions.mp4 155.3 MB
- 7. Basic Artificial Neural Networks - ANNs/27. Tensorboard.mp4 151.2 MB
- 7. Basic Artificial Neural Networks - ANNs/20. Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
- 7. Basic Artificial Neural Networks - ANNs/12. Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
- 12. Generative Adversarial Networks/4. Creating a GAN - Part Three - Model Training.mp4 138.0 MB
- 9. Recurrent Neural Networks - RNNs/11. RNN on a Time Series - Part Two.mp4 137.4 MB
- 13. Deployment/8. Live Deployment to the Web.mp4 132.7 MB
- 7. Basic Artificial Neural Networks - ANNs/23. Keras Project Solutions - Categorical Data.mp4 131.1 MB
- 11. AutoEncoders/3. Autoencoder for Dimensionality Reduction.mp4 123.2 MB
- 7. Basic Artificial Neural Networks - ANNs/17. Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
- 1. Course Overview, Installs, and Setup/2.1 FINAL_TF2_FILES.zip.zip 104.1 MB
- 1. Course Overview, Installs, and Setup/3.1 FINAL_TF2_FILES.zip.zip 104.1 MB
- 8. Convolutional Neural Networks - CNNs/7. CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
- 7. Basic Artificial Neural Networks - ANNs/21. Keras Project Solutions - Dealing with Missing Data.mp4 101.5 MB
- 11. AutoEncoders/4. Autoencoder for Images - Part One.mp4 98.7 MB
- 4. Pandas Crash Course/8. Data Input and Output.mp4 98.0 MB
- 5. Visualization Crash Course/3. Seaborn Basics.mp4 96.3 MB
- 01 Course Overview Installs and Setup/002 Course Setup and Installation.mp4 159.8 MB
- 13 Deployment/114 Flask Front End.mp4 156.9 MB
- 09 Recurrent Neural Networks - RNNs/088 Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
- 09 Recurrent Neural Networks - RNNs/087 RNN Exercise - Solutions.mp4 155.3 MB
- 07 Basic Artificial Neural Networks - ANNs/057 Tensorboard.mp4 151.2 MB
- 07 Basic Artificial Neural Networks - ANNs/050 Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
- 07 Basic Artificial Neural Networks - ANNs/042 Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
- 12 Generative Adversarial Networks/106 Creating a GAN - Part Three - Model Training.mp4 138.0 MB
- 09 Recurrent Neural Networks - RNNs/085 RNN on a Time Series - Part Two.mp4 137.4 MB
- 13 Deployment/115 Live Deployment to the Web.mp4 132.7 MB
- 07 Basic Artificial Neural Networks - ANNs/053 Keras Project Solutions - Categorical Data.mp4 131.1 MB
- 11 AutoEncoders/098 Autoencoder for Dimensionality Reduction.mp4 123.2 MB
- 07 Basic Artificial Neural Networks - ANNs/047 Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
- 01 Course Overview Installs and Setup/002 FINAL-TF2-FILES.zip 104.1 MB
- 01 Course Overview Installs and Setup/003 FINAL-TF2-FILES.zip 104.1 MB
- 08 Convolutional Neural Networks - CNNs/064 CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
- 07 Basic Artificial Neural Networks - ANNs/051 Keras Project Solutions - Dealing with Missing Data.mp4 101.5 MB
- 11 AutoEncoders/099 Autoencoder for Images - Part One.mp4 98.7 MB
- 04 Pandas Crash Course/017 Data Input and Output.mp4 98.0 MB
- 05 Visualization Crash Course/022 Seaborn Basics.mp4 96.3 MB
- [ FreeCourseWeb.com ] Hands-On Deep Learning Architectures with Python- Create deep neural networks to solve computational problems using TF and Keras.zip 90.3 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
- 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
- 7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
- 7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
- 4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB