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[FreeCourseSite.com] Udemy - Machine Learning, Data Science and Deep Learning with Python
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[FreeCourseSite.com] Udemy - Machine Learning, Data Science and Deep Learning with Python
磁力链接/BT种子简介
种子哈希:
5071a8b07c27b203f564c086f04ddf35f4d59a5b
文件大小:
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收录时间:
2021-03-17
最近下载:
2024-11-06
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文件列表
2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.mp4
155.0 MB
6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4
149.0 MB
10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.srt
148.5 MB
10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4
148.5 MB
8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.mp4
140.5 MB
5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4
139.0 MB
6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4
138.7 MB
7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4
135.7 MB
2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.mp4
135.6 MB
10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.mp4
134.5 MB
2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.mp4
131.2 MB
1. Getting Started/11. Introducing the Pandas Library [Optional].mp4
129.1 MB
8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4
123.6 MB
2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.mp4
122.4 MB
10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.mp4
120.9 MB
2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.mp4
119.6 MB
8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4
117.4 MB
2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.mp4
116.2 MB
6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4
115.1 MB
10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.mp4
113.9 MB
5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4
113.1 MB
8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4
110.8 MB
6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4
108.4 MB
8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4
108.0 MB
1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4
107.8 MB
7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4
107.3 MB
3. Predictive Models/1. [Activity] Linear Regression.mp4
105.3 MB
4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4
103.4 MB
8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp4
103.3 MB
11. Final Project/2. Final project review.mp4
103.3 MB
9. Experimental Design ML in the Real World/2. AB Testing Concepts.srt
102.2 MB
9. Experimental Design ML in the Real World/2. AB Testing Concepts.mp4
102.2 MB
1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4
101.2 MB
9. Experimental Design ML in the Real World/6. AB Test Gotchas.mp4
100.8 MB
4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.mp4
100.6 MB
5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp4
99.5 MB
10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).mp4
97.6 MB
10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.mp4
96.5 MB
8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp4
94.2 MB
4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4
93.4 MB
10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.mp4
92.5 MB
4. Machine Learning with Python/11. Decision Trees Concepts.mp4
90.7 MB
5. Recommender Systems/1. User-Based Collaborative Filtering.mp4
90.6 MB
10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp4
90.5 MB
5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp4
88.3 MB
8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp4
87.7 MB
9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.srt
85.6 MB
9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.mp4
85.6 MB
10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.mp4
85.3 MB
1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4
84.1 MB
10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp4
83.9 MB
7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp4
82.6 MB
6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4
81.7 MB
2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.mp4
81.0 MB
2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.mp4
79.0 MB
5. Recommender Systems/2. Item-Based Collaborative Filtering.mp4
78.6 MB
10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp4
77.8 MB
3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.mp4
77.4 MB
10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.mp4
76.2 MB
4. Machine Learning with Python/5. K-Means Clustering.mp4
75.4 MB
10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.mp4
72.9 MB
10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).mp4
72.5 MB
8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp4
72.2 MB
6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp4
71.0 MB
3. Predictive Models/2. [Activity] Polynomial Regression.mp4
70.0 MB
7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp4
69.5 MB
4. Machine Learning with Python/13. Ensemble Learning.mp4
68.4 MB
9. Experimental Design ML in the Real World/3. T-Tests and P-Values.mp4
68.1 MB
10. Deep Learning and Neural Networks/4. Deep Learning Details.srt
67.4 MB
10. Deep Learning and Neural Networks/4. Deep Learning Details.mp4
67.3 MB
12. You made it!/1. More to Explore.mp4
67.2 MB
2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.mp4
64.9 MB
1. Getting Started/1. Introduction.mp4
62.5 MB
2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.mp4
61.8 MB
4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4
61.0 MB
4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp4
60.1 MB
2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.mp4
58.9 MB
8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp4
57.4 MB
11. Final Project/1. Your final project assignment.mp4
54.1 MB
7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.mp4
51.4 MB
7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4
50.2 MB
3. Predictive Models/4. Multi-Level Models.mp4
49.8 MB
4. Machine Learning with Python/14. Support Vector Machines (SVM) Overview.mp4
46.9 MB
4. Machine Learning with Python/15. [Activity] Using SVM to cluster people using scikit-learn.mp4
46.1 MB
7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.mp4
43.7 MB
4. Machine Learning with Python/3. Bayesian Methods Concepts.mp4
42.7 MB
6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4
42.2 MB
10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.mp4
40.5 MB
7. Dealing with Real-World Data/5. Normalizing numerical data.mp4
40.1 MB
7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4
38.1 MB
7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp4
38.1 MB
4. Machine Learning with Python/7. Measuring Entropy.mp4
36.7 MB
9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.mp4
36.5 MB
10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.mp4
35.3 MB
9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.mp4
34.6 MB
1. Getting Started/7. Python Basics, Part 1 [Optional].mp4
34.6 MB
2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.mp4
31.5 MB
6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4
27.0 MB
2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.mp4
23.1 MB
1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].mp4
22.1 MB
1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].mp4
21.6 MB
1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4
20.7 MB
10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4
19.3 MB
6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.mp4
15.6 MB
4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.mp4
15.5 MB
1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].mp4
10.6 MB
4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.mp4
7.4 MB
4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.mp4
2.2 MB
2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.srt
30.7 kB
2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.srt
29.3 kB
6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.srt
29.2 kB
6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.srt
29.2 kB
2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.srt
29.1 kB
2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.srt
29.0 kB
8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.srt
28.8 kB
2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.srt
26.5 kB
2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.srt
26.5 kB
3. Predictive Models/1. [Activity] Linear Regression.srt
26.3 kB
7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt
25.1 kB
11. Final Project/2. Final project review.srt
25.1 kB
8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).srt
25.0 kB
7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.srt
24.4 kB
10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.srt
24.3 kB
10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.srt
23.9 kB
5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.srt
23.2 kB
10. Deep Learning and Neural Networks/5. Introducing Tensorflow.srt
23.0 kB
6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt
23.0 kB
4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.srt
23.0 kB
9. Experimental Design ML in the Real World/6. AB Test Gotchas.srt
22.4 kB
10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.srt
22.0 kB
10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.srt
22.0 kB
8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.srt
21.7 kB
6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.srt
21.7 kB
10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.srt
21.6 kB
3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.srt
21.6 kB
4. Machine Learning with Python/11. Decision Trees Concepts.srt
21.6 kB
4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.srt
21.4 kB
5. Recommender Systems/3. [Activity] Finding Movie Similarities.srt
20.6 kB
5. Recommender Systems/2. Item-Based Collaborative Filtering.srt
20.5 kB
10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).srt
20.3 kB
10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.srt
20.3 kB
6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.srt
20.2 kB
5. Recommender Systems/1. User-Based Collaborative Filtering.srt
19.8 kB
10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.srt
19.5 kB
1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt
19.3 kB
10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).srt
18.9 kB
1. Getting Started/11. Introducing the Pandas Library [Optional].srt
18.5 kB
8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.srt
18.2 kB
3. Predictive Models/2. [Activity] Polynomial Regression.srt
18.0 kB
4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt
17.8 kB
4. Machine Learning with Python/5. K-Means Clustering.srt
17.6 kB
7. Dealing with Real-World Data/3. Data Cleaning and Normalization.srt
17.5 kB
10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.srt
17.2 kB
5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.srt
17.2 kB
2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.srt
16.6 kB
2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.srt
16.5 kB
9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.srt
15.8 kB
2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.srt
15.4 kB
4. Machine Learning with Python/15. [Activity] Using SVM to cluster people using scikit-learn.srt
15.2 kB
1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt
15.0 kB
4. Machine Learning with Python/13. Ensemble Learning.srt
14.9 kB
1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt
14.8 kB
7. Dealing with Real-World Data/1. BiasVariance Tradeoff.srt
14.7 kB
7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.srt
14.7 kB
7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt
14.6 kB
8. Apache Spark Machine Learning on Big Data/10. TF IDF.srt
14.4 kB
8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt
14.2 kB
10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.srt
14.2 kB
10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.srt
14.1 kB
5. Recommender Systems/6. [Exercise] Improve the recommender's results.srt
13.5 kB
9. Experimental Design ML in the Real World/3. T-Tests and P-Values.srt
13.5 kB
4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt
13.4 kB
2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.srt
13.3 kB
8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.srt
13.2 kB
6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.srt
12.6 kB
8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.srt
12.3 kB
10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.srt
12.3 kB
7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.srt
12.1 kB
11. Final Project/1. Your final project assignment.srt
11.8 kB
4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.srt
11.8 kB
2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.srt
11.8 kB
8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.srt
11.7 kB
7. Dealing with Real-World Data/6. [Activity] Detecting outliers.srt
11.7 kB
6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt
11.1 kB
3. Predictive Models/4. Multi-Level Models.srt
10.9 kB
8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.srt
10.8 kB
4. Machine Learning with Python/14. Support Vector Machines (SVM) Overview.srt
10.1 kB
7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt
10.1 kB
6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.srt
9.9 kB
6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.srt
9.2 kB
4. Machine Learning with Python/3. Bayesian Methods Concepts.srt
9.0 kB
9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.srt
8.5 kB
10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt
8.5 kB
1. Getting Started/7. Python Basics, Part 1 [Optional].srt
7.9 kB
7. Dealing with Real-World Data/5. Normalizing numerical data.srt
7.8 kB
1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].srt
7.8 kB
2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.srt
7.8 kB
12. You made it!/3. Bonus Lecture More courses to explore!.html
7.5 kB
12. You made it!/1. More to Explore.srt
7.4 kB
4. Machine Learning with Python/7. Measuring Entropy.srt
7.1 kB
1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].srt
6.1 kB
1. Getting Started/1. Introduction.srt
4.9 kB
1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].srt
4.3 kB
1. Getting Started/2. Udemy 101 Getting the Most From This Course.srt
4.1 kB
2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.srt
4.1 kB
8. Apache Spark Machine Learning on Big Data/2. Spark installation notes for MacOS and Linux users.html
3.6 kB
10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.srt
3.2 kB
4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.srt
1.3 kB
4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.srt
1.1 kB
10. Deep Learning and Neural Networks/6. Important note about Tensorflow 2.html
1.0 kB
4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.srt
689 Bytes
8. Apache Spark Machine Learning on Big Data/1. Warning about Java 11 and Spark 2.4!.html
650 Bytes
12. You made it!/2. Don't Forget to Leave a Rating!.html
564 Bytes
1. Getting Started/3. Installation Getting Started.html
265 Bytes
6. More Data Mining and Machine Learning Techniques/6.2 Pac-Man Example.html
145 Bytes
6. More Data Mining and Machine Learning Techniques/6.1 Cat and Mouse Example.html
140 Bytes
0. Websites you may like/[FCS Forum].url
133 Bytes
0. Websites you may like/[FreeCourseSite.com].url
127 Bytes
0. Websites you may like/[CourseClub.ME].url
122 Bytes
6. More Data Mining and Machine Learning Techniques/6.3 Python Markov Decision Process Toolbox.html
119 Bytes
8. Apache Spark Machine Learning on Big Data/3.1 winutils.exe.html
108 Bytes
8. Apache Spark Machine Learning on Big Data/4.1 winutils.exe.html
108 Bytes
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