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O'Reilly - Advanced Machine Learning with scikit learn

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O'Reilly - Advanced Machine Learning with scikit learn

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Name:O'Reilly - Advanced Machine Learning with scikit learn

Infohash: 8B5BA4584FA0B9BD459AF22AD82B5C78FA440807

Total Size: 765.84 MB

Seeds: 0

Leechers: 0

Stream: Watch Full Movie @ Movie4u

Last Updated: 2024-05-23 12:48:33 (Update Now)

Torrent added: 2015-11-01 13:04:22






Torrent Files List


01. Introduction (Size: 765.84 MB) (Files: 47)

 01. Introduction

  01_01-What To Expect And About The Author.mp4

12.51 MB

  01_02-Setup.mp4

5.86 MB

  01_03-The Classifier Interface.mp4

27.18 MB

  01_04-The Regressor Interface.mp4

10.81 MB

  01_05-The Transformer Interface.mp4

7.90 MB

  01_06-The Cluster Interface.mp4

22.34 MB

  01_07-The Manifold Interface.mp4

10.96 MB

  01_08-scikitLearn Interface Summary.mp4

11.31 MB

  01_09-CrossValidation With Cross_Val_Score.mp4

20.32 MB

  01_10-Parameter Searches With GridSearchCV.mp4

19.34 MB

  01_11-How To Access Your Working Files.mp4

26.38 MB

 02. Model Complexity, Overfitting And Underfitting

  02_01-What Is Model Complexity And Overfitting.mp4

7.25 MB

  02_02-Linear Models InDepth.mp4

33.58 MB

  02_03-Kernel SVMs InDepth.mp4

21.89 MB

  02_04-Random Forests InDepth.mp4

15.13 MB

  02_05-Learning Curves For Analyzing Model Complexity.mp4

12.64 MB

  02_06-Validation Curves For Analyzing Model Parameters.mp4

7.61 MB

  02_07-Efficient Parameter Search With EstimatorCV Objects.mp4

18.08 MB

 03. Pipelines

  03_01-Motivation Of Using Pipelines.mp4

9.69 MB

  03_02-Defining A Pipeline And Basic Usage.mp4

19.08 MB

  03_03-CrossValidation With Pipelines.mp4

7.76 MB

  03_04-Parameter Selection With Pipelines.mp4

16.74 MB

 04. Advanced Metrics And Imbalanced Classes

  04_01-Be Mindful Of Default Metrics.mp4

20.60 MB

  04_02-More Evaluation Methods For Classification.mp4

14.57 MB

  04_03-AUC.mp4

19.69 MB

  04_04-Defining Custom Metrics.mp4

20.44 MB

 05. Model Selection For Unsupervised Learning

  05_01-Guidelines For Unsupervised Model Selection.mp4

21.63 MB

  05_02-Model Selection For Density Models.mp4

18.17 MB

  05_03-Model Selection For Clustering.mp4

14.02 MB

 06. Dealing With Categorical Variables, Dictionaries, And Incomplete Data

  06_01-Why Real Data Is Messy.mp4

19.04 MB

  06_02-OneHot Encoding For Categorical Data.mp4

18.12 MB

  06_03-Working With Dictionaries.mp4

6.42 MB

  06_04-Handling Incomplete Data.mp4

14.68 MB

 07. Handling Text Data

  07_01-Motivation.mp4

8.03 MB

  07_02-BagOfWords Representations.mp4

19.10 MB

  07_03-Text Classification For Sentiment Analysis Part 1.mp4

25.36 MB

  07_04-Text Classification For Sentiment Analysis Part 2.mp4

12.97 MB

  07_05-The Hashing Trick.mp4

9.11 MB

  07_06-Other Representations Distributed Word Representations.mp4

5.08 MB

 08. Out Of Core Learning

  08_01-The TradeOffs Of Out Of Core Learning.mp4

10.80 MB

  08_02-The scikitLearn Interface For Out Of Core Learning.mp4

14.67 MB

  08_03-Kernel Approximations For LargeScale NonLinear Classification.mp4

16.04 MB

  08_04-Subsample And Transform Supervised Transformations For Out Of Core Learning.mp4

18.35 MB

  08_05-Application OutOfCore Text Classification.mp4

18.40 MB

 09. Conclusion

  09_01-Summary.mp4

10.07 MB

  09_02-Where To Go From Here.mp4

8.62 MB

 Working Files

  Advanced_Machine_Learning_with_scikit_learn_Working_Files.zip

57.48 MB
 

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