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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
607.37Кб |
| 01 - Programming Foundations of Classification and Regression LiveLessons (Machine Learning with Python for Everyone Series), Part 1 (Video Training) - Introduction.mp4 |
141.57Мб |
| 02 - Topics.mp4 |
14.87Мб |
| 03 - 1.1 Environment Installation.mp4 |
184.76Мб |
| 04 - 1.2 Three Things You Can do with NumPy and matplotlib.mp4 |
283.13Мб |
| 05 - 1.3 Three Things You Can Do with Pandas.mp4 |
263.92Мб |
| 06 - 1.4 Three Things You Can Do with scikit-learn and Friends.mp4 |
242.64Мб |
| 07 - Topics.mp4 |
17.35Мб |
| 08 - 2.1 Probability.mp4 |
144.01Мб |
| 09 - 2.2 Distributions.mp4 |
197.95Мб |
| 1 |
161.34Кб |
| 10 |
84.44Кб |
| 10 - 2.3 Linear Combinations.mp4 |
464.41Мб |
| 11 |
687.00Кб |
| 11 - 2.4 Geometry, Part 1.mp4 |
291.94Мб |
| 12 |
368.98Кб |
| 12 - 2.5 Geometry, Part 2.mp4 |
379.76Мб |
| 13 |
160.66Кб |
| 13 - 2.6 Geometry, Part 3.mp4 |
116.65Мб |
| 14 |
548.94Кб |
| 14 - 2.7 When Computers and Math Meet.mp4 |
198.01Мб |
| 15 |
881.87Кб |
| 15 - Topics.mp4 |
14.51Мб |
| 16 |
735.12Кб |
| 16 - 3.1 Setup and the Iris Dataset.mp4 |
227.14Мб |
| 17 |
802.99Кб |
| 17 - 3.2 Accuracy.mp4 |
128.93Мб |
| 18 |
1016.66Кб |
| 18 - 3.3 k-Nearest Neighbors.mp4 |
189.39Мб |
| 19 |
52.85Кб |
| 19 - 3.4 Train Test Splitting and Fitting k-NN.mp4 |
363.87Мб |
| 2 |
534.41Кб |
| 20 |
626.68Кб |
| 20 - 3.5 Naive Bayes.mp4 |
349.40Мб |
| 21 |
243.65Кб |
| 21 - Topics.mp4 |
14.59Мб |
| 22 |
903.62Кб |
| 22 - 4.1 Learning Evaluation.mp4 |
135.75Мб |
| 23 |
633.31Кб |
| 23 - 4.2 Resource Evaluation - Time.mp4 |
203.22Мб |
| 24 |
1009.25Кб |
| 24 - 4.3 Resource Evaluation - Memory.mp4 |
229.46Мб |
| 25 |
441.26Кб |
| 25 - 4.4 Scripts.mp4 |
402.48Мб |
| 26 |
252.20Кб |
| 26 - Topics.mp4 |
13.41Мб |
| 27 |
653.25Кб |
| 27 - 5.1 Setup and the Diabetes Dataset.mp4 |
291.86Мб |
| 28 |
74.57Кб |
| 28 - 5.2 Measures of Center.mp4 |
165.12Мб |
| 29 |
361.33Кб |
| 29 - 5.3 k-Nearest Neighbors for Regression.mp4 |
260.33Мб |
| 3 |
241.67Кб |
| 30 |
32.19Кб |
| 30 - 5.4 Linear Regression, Part 1.mp4 |
451.84Мб |
| 31 |
668.09Кб |
| 31 - 5.5 Linear Regression, Part 2.mp4 |
161.38Мб |
| 32 |
137.14Кб |
| 32 - Topics.mp4 |
11.25Мб |
| 33 |
416.49Кб |
| 33 - 6.1 Optimization, Part 1.mp4 |
373.61Мб |
| 34 |
496.67Кб |
| 34 - 6.2 Optimization, Part 2.mp4 |
210.28Мб |
| 35 |
599.95Кб |
| 35 - 6.3 Learning Performance.mp4 |
129.36Мб |
| 36 - 6.4 Resource Evaluation.mp4 |
235.84Мб |
| 37 - Programming Foundations of Classification and Regression LiveLessons (Machine Learning with Python for Everyone Series), Part 1 (Video Training) - Summary.mp4 |
31.97Мб |
| 4 |
397.62Кб |
| 5 |
128.08Кб |
| 6 |
612.08Кб |
| 7 |
56.37Кб |
| 8 |
147.35Кб |
| 9 |
892.23Кб |
| TutsNode.com.txt |
63б |