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O’REILLY | Data Science Bookcamp, Video Edition [FCO]
Seeders :
8
Leechers :
8
Downloads :
59
Size :
6.4 GB
Uploaded :
15 May, 2022
Uploader :
one
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Info hash: 68f1b06f13a8d2daa4491ee1d44b6731ac249612
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O’REILLY | Data Science Bookcamp, Video Edition [FCO]
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O’REILLY | Data Science Bookcamp, Video Edition [FCO]
6.4 GB
1 - Case study 1 - Finding the winning strategy in a card game.mp4
6.9 MB
10 - Chapter 3. Using permutations to shuffle cards.mp4
35.4 MB
100 - Chapter 20. Network-driven supervised machine learning.mp4
49.0 MB
101 - Chapter 20. The basics of supervised machine learning.mp4
49.2 MB
102 - Chapter 20. Measuring predicted label accuracy, Part 1.mp4
37.3 MB
103 - Chapter 20. Measuring predicted label accuracy, Part 2.mp4
55.2 MB
104 - Chapter 20. Optimizing KNN performance.mp4
35.7 MB
105 - Chapter 20. Running a grid search using scikit-learn.mp4
39.3 MB
106 - Chapter 20. Limitations of the KNN algorithm.mp4
63.2 MB
107 - Chapter 21. Training linear classifiers with logistic regression.mp4
58.3 MB
108 - Chapter 21. Training a linear classifier, Part 1.mp4
43.5 MB
109 - Chapter 21. Training a linear classifier, Part 2.mp4
73.3 MB
11 - Chapter 4. Case study 1 solution.mp4
34.3 MB
110 - Chapter 21. Improving linear classification with logistic regression, Part 1.mp4
43.4 MB
111 - Chapter 21. Improving linear classification with logistic regression, Part 2.mp4
43.1 MB
112 - Chapter 21. Training linear classifiers using scikit-learn.mp4
49.6 MB
113 - Chapter 21. Measuring feature importance with coefficients.mp4
93.1 MB
114 - Chapter 22. Training nonlinear classifiers with decision tree techniques.mp4
65.2 MB
115 - Chapter 22. Training a nested if_else model using two features.mp4
53.3 MB
116 - Chapter 22. Deciding which feature to split on.mp4
57.2 MB
117 - Chapter 22. Training if_else models with more than two features.mp4
57.8 MB
118 - Chapter 22. Training decision tree classifiers using scikit-learn.mp4
51.9 MB
119 - Chapter 22. Studying cancerous cells using feature importance.mp4
59.3 MB
12 - Chapter 4. Optimizing strategies using the sample space for a 10-card deck.mp4
47.1 MB
120 - Chapter 22. Improving performance using random forest classification.mp4
57.4 MB
121 - Chapter 22. Training random forest classifiers using scikit-learn.mp4
53.0 MB
122 - Chapter 23. Case study 5 solution.mp4
32.9 MB
123 - Chapter 23. Exploring the experimental observations.mp4
39.0 MB
124 - Chapter 23. Training a predictive model using network features, Part 1.mp4
52.6 MB
125 - Chapter 23. Training a predictive model using network features, Part 2.mp4
53.9 MB