种子简介

种子名称： [DesireCourse.Net] Udemy - Machine Learning, incl. Deep Learning, with R
文件类型： 视频
文件数目： 142个文件
文件大小： 7.26 GB
收录时间： 2019-11-4 19:16
已经下载： 3次
资源热度： 149
最近下载： 2024-11-19 19:28

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:d5ce2fe57610935eb092ba56c6961a76bf1ab5c9&dn=[DesireCourse.Net] Udemy - Machine Learning, incl. Deep Learning, with R 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[DesireCourse.Net] Udemy - Machine Learning, incl. Deep Learning, with R.torrent

1. Introduction/1. Course Overview.mp410.37MB

1. Introduction/2. AI 101.mp429.52MB

1. Introduction/3. Machine Learning 101.mp431.15MB

1. Introduction/4. Models.mp427.65MB

1. Introduction/5. Teaser Overview.mp46.24MB

1. Introduction/6. Teaser Lab.mp4126.51MB

10. Random Forests/1. Random Forests 101.mp410.82MB

10. Random Forests/2. Random Forests Interactive.mp417.53MB

10. Random Forests/3. Random Forest Lab (Intro).mp414.84MB

10. Random Forests/4. Random Forest Lab (Coding 12).mp4109.85MB

10. Random Forests/5. Random Forest Lab (Coding 22).mp4107.1MB

10. Random Forests/6. Random Forest Exercise.mp422.07MB

11. Logistic Regression/1. Logistic Regression 101.mp427.64MB

11. Logistic Regression/2. Logistic Regression Lab (Intro).mp48.79MB

11. Logistic Regression/3. Logistic Regression Lab (Coding 12).mp491.93MB

11. Logistic Regression/4. Logistic Regression Lab (Coding 22).mp463.11MB

11. Logistic Regression/5. Logistic Regression Exercise.mp410.68MB

12. Support Vector Machines/1. Support Vector Machines 101.mp421.84MB

12. Support Vector Machines/2. Support Vector Machines Lab (Intro).mp413.6MB

12. Support Vector Machines/3. Support Vector Machines Lab (Coding 12).mp478.82MB

12. Support Vector Machines/4. Support Vector Machines Lab (Coding 22).mp442.15MB

12. Support Vector Machines/5. Support Vector Machines Exercise.mp421.2MB

13. Ensemble Models/1. Ensemble Models 101.mp412.06MB

14. ----- Association Rules -----/1. Association Rules 101.mp420.87MB

14. ----- Association Rules -----/2. How to get the code.mp48.83MB

15. Apriori/1. Apriori 101.mp429.9MB

15. Apriori/2. Apriori Lab (Intro).mp418.09MB

15. Apriori/3. Apriori Lab (Coding 12).mp473.35MB

15. Apriori/4. Apriori Lab (Coding 22).mp4113.44MB

15. Apriori/5. Apriori Exercise.mp417.25MB

15. Apriori/6. Apriori Solution.mp4100.14MB

16. ----- Clustering -----/1. Clustering Overview.mp410.12MB

16. ----- Clustering -----/2. How to get the code.mp48.81MB

17. kmeans/1. kmeans 101.mp431.74MB

17. kmeans/2. kmeans Lab.mp4159.88MB

17. kmeans/3. kmeans Exercise.mp427.55MB

17. kmeans/4. kmeans Solution.mp4106.36MB

18. Hierarchical Clustering/1. Hierarchical Clustering 101.mp432.4MB

18. Hierarchical Clustering/2. Hierarchical Clustering Interactive.mp434.11MB

18. Hierarchical Clustering/3. Hierarchical Clustering Lab.mp4189.25MB

19. Dbscan/1. Dbscan 101.mp431.32MB

19. Dbscan/2. Dbscan Lab.mp4111.43MB

2. R Refresher/1. R and RStudio Installation.mp4102.32MB

2. R Refresher/2. How to get the code.mp48.83MB

2. R Refresher/3. Rmarkdown Lab.mp465.81MB

2. R Refresher/4. Piping 101.mp49.41MB

2. R Refresher/5. Data Manipulation Lab.mp4104.59MB

2. R Refresher/6. Data Reshaping 101.mp418.81MB

2. R Refresher/7. Data Reshaping Lab.mp4103.14MB

2. R Refresher/8. Packages Preparation Lab.mp412.32MB

21. Principal Component Analysis (PCA)/1. PCA 101.mp441.79MB

21. Principal Component Analysis (PCA)/2. PCA Lab.mp4126.99MB

21. Principal Component Analysis (PCA)/3. PCA Exercise.mp415.24MB

21. Principal Component Analysis (PCA)/4. PCA Solution.mp480.96MB

22. t-SNE/1. t-SNE 101.mp419.97MB

22. t-SNE/2. t-SNE Lab (Sphere).mp457.38MB

22. t-SNE/3. t-SNE Lab (Mnist).mp470.37MB

23. Factor Analysis/1. Factor Analysis 101.mp434.98MB

23. Factor Analysis/2. Factor Analysis Lab (Intro).mp416.51MB

23. Factor Analysis/3. Factor Analysis Lab (Coding 12).mp478.66MB

23. Factor Analysis/4. Factor Analysis Lab (Coding 22).mp491.7MB

23. Factor Analysis/5. Factor Analysis Exercise.mp413.23MB

24. ----- Reinforcement Learning -----/1. Reinforcement Learning 101.mp437.44MB

24. ----- Reinforcement Learning -----/2. Upper Confidence Bound 101.mp450.41MB

24. ----- Reinforcement Learning -----/3. Upper Confidence Bound Interactive.mp446.49MB

24. ----- Reinforcement Learning -----/4. How to get the code.mp48.83MB

24. ----- Reinforcement Learning -----/5. Upper Confidence Bound Lab (Intro).mp413.12MB

24. ----- Reinforcement Learning -----/6. Upper Confidence Bound Lab (Coding 12).mp4138.26MB

24. ----- Reinforcement Learning -----/7. Upper Confidence Bound Lab (Coding 22).mp467.11MB

25. ----- Deep Learning -----/1. Deep Learning General Overview.mp426.37MB

25. ----- Deep Learning -----/10. How to get the code.mp48.82MB

25. ----- Deep Learning -----/11. Python and Keras Installation.mp472.66MB

25. ----- Deep Learning -----/2. Deep Learning Modeling 101.mp412.39MB

25. ----- Deep Learning -----/3. Performance.mp411.16MB

25. ----- Deep Learning -----/4. From Perceptron to Neural Networks.mp419.76MB

25. ----- Deep Learning -----/5. Layer Types.mp421.74MB

25. ----- Deep Learning -----/6. Activation Functions.mp420.74MB

25. ----- Deep Learning -----/7. Loss Function.mp413.88MB

25. ----- Deep Learning -----/8. Optimizer.mp422.33MB

25. ----- Deep Learning -----/9. Deep Learning Frameworks.mp49.47MB

26. Deep Learning Regression/1. Multi-Target Regression Lab (Intro).mp413.33MB

26. Deep Learning Regression/2. Multi-Target Regression Lab (Coding 12).mp4119.06MB

26. Deep Learning Regression/3. Multi-Target Regression Lab (Coding 22).mp498.84MB

27. Deep Learning Classification/1. Binary Classification Lab (Intro).mp415.28MB

27. Deep Learning Classification/2. Binary Classification Lab (Coding 12).mp4121.03MB

27. Deep Learning Classification/3. Binary Classification Lab (Coding 22).mp467.87MB

27. Deep Learning Classification/4. Multi-Label Classification Lab (Intro).mp424.42MB

27. Deep Learning Classification/5. Multi-Label Classification Lab (Coding 13).mp4109.73MB

27. Deep Learning Classification/6. Multi-Label Classification Lab (Coding 23).mp4128.81MB

27. Deep Learning Classification/7. Multi-Label Classification Lab (Coding 33).mp462.74MB

28. Convolutional Neural Networks/1. Convolutional Neural Networks 101.mp444.26MB

28. Convolutional Neural Networks/2. Convolutional Neural Networks Interactive.mp418.16MB

28. Convolutional Neural Networks/3. Convolutional Neural Networks Lab (Intro).mp412.13MB

28. Convolutional Neural Networks/4. Convolutional Neural Networks Lab (Coding).mp4189.77MB

28. Convolutional Neural Networks/5. Convolutional Neural Networks Exercise.mp423.73MB

28. Convolutional Neural Networks/6. Semantic Segmentation 101.mp457.94MB

28. Convolutional Neural Networks/7. Semantic Segmentation Lab (Intro).mp425.49MB

28. Convolutional Neural Networks/8. Semantic Segmentation Lab (Coding).mp425.48MB

29. Autoencoders/1. Autoencoders 101.mp416.71MB

29. Autoencoders/2. Autoencoders Lab (Intro).mp415.11MB

29. Autoencoders/3. Autoencoders Lab (Coding).mp4105.45MB

3. ----- Regression, Model Preparation, and Regularization -----/2. How to get the code.mp48.83MB

30. Transfer Learning and Pretrained Models/1. Transfer Learning and Pretrained Models 101.mp432.78MB

30. Transfer Learning and Pretrained Models/2. Transfer Learning and Pretrained Models Lab (Introduction).mp413.63MB

30. Transfer Learning and Pretrained Models/3. Transfer Learning and Pretrained Models Lab (Coding).mp499.41MB

31. Recurrent Neural Networks/1. Recurrent Neural Networks 101.mp429.49MB

31. Recurrent Neural Networks/2. LSTM Univariate, Multistep Timeseries Prediction (Intro).mp413.62MB

31. Recurrent Neural Networks/3. LSTM Univariate, Multistep Timeseries Prediction (Coding).mp4146.57MB

31. Recurrent Neural Networks/4. LSTM Multivariate, Multistep Timeseries Prediction (Intro).mp412.02MB

31. Recurrent Neural Networks/5. LSTM Multivariate, Multistep Timeseries Prediction (Coding).mp4141.53MB

4. Regression/1. Regression Types 101.mp417.74MB

4. Regression/10. Multivariate Regression Lab.mp4135.7MB

4. Regression/11. Multivariate Regression Exercise.mp413.69MB

4. Regression/12. Multivariate Regression Solution.mp4122.64MB

4. Regression/2. Univariate Regression 101.mp425.59MB

4. Regression/3. Univariate Regression Interactive.mp421.85MB

4. Regression/4. Univariate Regression Lab.mp488.4MB

4. Regression/5. Univariate Regression Exercise.mp418.16MB

4. Regression/6. Univariate Regression Solution.mp471.32MB

4. Regression/7. Polynomial Regression 101.mp411.35MB

4. Regression/8. Polynomial Regression Lab.mp4117.62MB

4. Regression/9. Multivariate Regression 101.mp422.44MB

5. Model Preparation and Evaluation/1. Underfitting Overfitting 101.mp456.1MB

5. Model Preparation and Evaluation/2. Train Validation Test Split 101.mp413.51MB

5. Model Preparation and Evaluation/3. Train Validation Test Split Interactive.mp436MB

5. Model Preparation and Evaluation/4. Train Validation Test Split Lab.mp4117.4MB

5. Model Preparation and Evaluation/5. Resampling Techniques 101.mp417.2MB

5. Model Preparation and Evaluation/6. Resampling Techniques Lab.mp4188.6MB

6. Regularization/1. Regularization 101.mp423.77MB

6. Regularization/2. Regularization Lab.mp4189.57MB

7. ----- Classification -----/2. How to get the code.mp48.84MB

8. Classification Basics/1. Confusion Matrix 101.mp428.88MB

8. Classification Basics/2. ROC Curve 101.mp448.01MB

8. Classification Basics/3. ROC Curve Interactive.mp443.5MB

8. Classification Basics/4. ROC Curve Lab Intro.mp412.6MB

8. Classification Basics/5. ROC Curve Lab 13 (Data Prep, Modeling).mp4118.06MB

8. Classification Basics/6. ROC Curve Lab 23 (Confusion Matrix and ROC).mp470.79MB

8. Classification Basics/7. ROC Curve Lab 33 (ROC, AUC, Cost Function).mp4135.48MB

9. Decision Trees/1. Decision Trees 101.mp420.53MB

9. Decision Trees/2. Decision Trees Lab (Intro).mp410.63MB

9. Decision Trees/3. Decision Trees Lab (Coding).mp4121.02MB

9. Decision Trees/4. Decision Trees Exercise.mp414.13MB