|
Обратите внимание, что наш сайт не размещает какие-либо файлы из списка. Вы не можете скачать
эти файлы или скачать torrent-файл.
|
| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
69.47Кб |
| 1 |
100.54Кб |
| 10 |
419.96Кб |
| 10 - 02 Type Conversion Examples.mp4 |
59.84Мб |
| 1 - 01 Introduction To Recommender Systems.mp4 |
33.42Мб |
| 11 |
627.06Кб |
| 11 - 03 Operators.mp4 |
161.46Мб |
| 12 |
584.64Кб |
| 12 - 04 Collections.mp4 |
41.63Мб |
| 13 |
735.22Кб |
| 13 - 05 List Examples.mp4 |
109.75Мб |
| 14 |
572.12Кб |
| 14 - 06 Tuples Examples.mp4 |
52.40Мб |
| 15 |
94.24Кб |
| 15 - 07 Dictionaries Examples.mp4 |
87.28Мб |
| 16 |
402.52Кб |
| 16 - 09 Conditionals.mp4 |
38.05Мб |
| 17 |
494.07Кб |
| 17 - 10 If Statement Examples.mp4 |
118.03Мб |
| 18 |
87.79Кб |
| 18 - 11 Loops.mp4 |
167.03Мб |
| 19 |
1023.73Кб |
| 19 - 12 Functions.mp4 |
86.44Мб |
| 2 |
557.19Кб |
| 20 |
1006.55Кб |
| 20 - 13 Parameters And Return Values Examples.mp4 |
78.52Мб |
| 2 - 02 How To Evaluate Recommender Systems.mp4 |
51.03Мб |
| 21 |
366.33Кб |
| 21 - 14 Classes And Objects.mp4 |
223.26Мб |
| 22 |
120.37Кб |
| 22 - 15 Inheritance Examples.mp4 |
130.64Мб |
| 23 |
26.11Кб |
| 23 - 16 Static Members Examples.mp4 |
78.61Мб |
| 24 |
474.33Кб |
| 24 - 17 Summary And Outro.mp4 |
20.84Мб |
| 25 |
162.35Кб |
| 25 - Source Code.html |
27б |
| 26 |
994.02Кб |
| 26 - 01 Load Data As Pandas Dataframes.mp4 |
95.71Мб |
| 27 |
410.50Кб |
| 27 - 02 Merge Movies And Ratings Dataframes.mp4 |
58.60Мб |
| 28 |
592.01Кб |
| 28 - 03 Build A Correlation Matrix.mp4 |
45.47Мб |
| 29 |
802.22Кб |
| 29 - 04 Test The Recommender.mp4 |
49.61Мб |
| 3 |
363.55Кб |
| 30 |
212.39Кб |
| 3 - 03 Content Based Recommendations.mp4 |
17.88Мб |
| 30 - Source Files.html |
27б |
| 30 - SourceFiles.zip |
1.65Мб |
| 31 |
212.44Кб |
| 31 - 00 Project Preview.mp4 |
19.30Мб |
| 32 |
930.71Кб |
| 32 - 00A What Is Machine Learning.mp4 |
27.70Мб |
| 33 |
892.63Кб |
| 33 - 00B Types Of Machine Learning Models.mp4 |
52.53Мб |
| 34 |
486.30Кб |
| 34 - 00C What Is Supervised Learning.mp4 |
59.03Мб |
| 35 |
613.16Кб |
| 35 - 01 Load Data Into Dataframes.mp4 |
49.77Мб |
| 36 |
991.54Кб |
| 36 - 02 Find A Recommendation Based On Different Movie Features.mp4 |
104.47Мб |
| 37 |
230.91Кб |
| 37 - 03 Calculate Distance Between Users.mp4 |
34.97Мб |
| 38 |
396.26Кб |
| 38 - 04 Find Similar Users With Euclidean Distance.mp4 |
47.44Мб |
| 39 |
121.31Кб |
| 39 - Source Files.html |
27б |
| 39 - SourceFiles.zip |
1.66Мб |
| 4 |
142.25Кб |
| 40 |
572.71Кб |
| 40 - 05 Define Similarity Between Users.mp4 |
37.19Мб |
| 4 - 04 Neighborhood Based Collaborative Filtering.mp4 |
14.34Мб |
| 41 |
852.13Кб |
| 41 - 06 Find Top Similar Users.mp4 |
47.17Мб |
| 42 |
539.83Кб |
| 42 - 07 Recommend A Movie Based On User Similarity.mp4 |
42.77Мб |
| 43 |
315.54Кб |
| 43 - Source Files.html |
27б |
| 43 - SourceFiles.zip |
851.30Кб |
| 44 |
237.43Кб |
| 44 - 08A What Is K Nearest Neighbours.mp4 |
37.61Мб |
| 45 |
806.83Кб |
| 45 - 08B Recommend A Movie With A K Nearest Neighbors Classifier.mp4 |
70.88Мб |
| 46 |
121.07Кб |
| 46 - 09 Create A Sample User For Testing.mp4 |
55.09Мб |
| 47 |
377.59Кб |
| 47 - 10 Recommend Movies To Sample User.mp4 |
20.54Мб |
| 48 |
203.85Кб |
| 48 - Source Files.html |
27б |
| 48 - SourceFiles.zip |
852.74Кб |
| 49 |
550.28Кб |
| 49 - 00 Project Preview.mp4 |
14.23Мб |
| 5 |
257.46Кб |
| 50 |
401.70Кб |
| 50 - 01 Load Data For Machine Learning.mp4 |
105.86Мб |
| 51 |
975.41Кб |
| 51 - 02 Process Data For Machine Learning.mp4 |
77.91Мб |
| 52 |
398.42Кб |
| 52 - 03 Build Categories.mp4 |
55.79Мб |
| 53 |
830.73Кб |
| 53 - Source Files.html |
27б |
| 53 - SourceFiles.zip |
889.97Кб |
| 54 |
144.14Кб |
| 54 - 04A Regression Introduction.mp4 |
35.86Мб |
| 55 |
30.27Кб |
| 55 - 04B What Is Regression.mp4 |
85.08Мб |
| 56 |
123.92Кб |
| 56 - 04C Build A Ridge Regression Model.mp4 |
72.64Мб |
| 57 |
589.37Кб |
| 57 - 05 Evaluate Model Error.mp4 |
48.88Мб |
| 58 |
154.19Кб |
| 58 - 06 Visualize Top Features Affecting Rating.mp4 |
58.42Мб |
| 59 |
304.96Кб |
| 59 - 07 Build A Lasso Regression Model.mp4 |
55.79Мб |
| 5 - Source Files.html |
27б |
| 5 - SourceFiles.zip |
4.60Мб |
| 6 |
565.84Кб |
| 60 |
160.52Кб |
| 60 - 08 Visualize Top Features From Lasso Regression.mp4 |
42.21Мб |
| 6 - 00 About Mammoth Interactive.mp4 |
8.64Мб |
| 61 |
475.86Кб |
| 61 - 09 Determine Which Model Is Best.mp4 |
17.02Мб |
| 62 |
901.13Кб |
| 62 - Source Files.html |
27б |
| 62 - SourceFiles.zip |
1.84Мб |
| 63 |
718.16Кб |
| 63 - 01 Load Data For A Neural Network.mp4 |
62.97Мб |
| 64 |
125.28Кб |
| 64 - 02 Build A Singular Value Decomposition Algorithm.mp4 |
73.02Мб |
| 65 |
1001.09Кб |
| 65 - 03 Calculate Model Error.mp4 |
62.54Мб |
| 66 |
677.11Кб |
| 66 - Source Files.html |
27б |
| 66 - SourceFIles.zip |
1.33Мб |
| 67 |
787.23Кб |
| 67 - 01 What Is Deep Learning.mp4 |
34.88Мб |
| 68 |
990.82Кб |
| 68 - 02 What Is A Neural Network.mp4 |
39.61Мб |
| 69 |
369.65Кб |
| 69 - 03 What Is Unsupervised Learning.mp4 |
40.80Мб |
| 7 |
143.18Кб |
| 70 |
413.21Кб |
| 70 - 04 Build A Neural Network.mp4 |
95.59Мб |
| 7 - 01 How To Learn Online Effectively.mp4 |
74.00Мб |
| 71 |
163.04Кб |
| 71 - 05 Train The Neural Network.mp4 |
87.43Мб |
| 72 |
350.89Кб |
| 72 - Source File.html |
27б |
| 72 - SourceFiles.zip |
683.92Кб |
| 73 |
355.73Кб |
| 73 - 00 Project Preview.mp4 |
14.03Мб |
| 74 |
359.68Кб |
| 74 - 01 Load Data Into Dataframes.mp4 |
44.69Мб |
| 75 - 02 Explore Data In Our Dataset.mp4 |
20.12Мб |
| 76 - 03 Build A Rating Pivot Table.mp4 |
30.85Мб |
| 77 - 04 Calculate Average Rating Of A Movie.mp4 |
41.88Мб |
| 78 - 05 Find Ratings For A Movie In Every Slice.mp4 |
40.46Мб |
| 79 - 06 Find Rating Averages For Every Movie In The Slice.mp4 |
54.13Мб |
| 8 |
537.80Кб |
| 80 - 07 Build An Average Ratings Column.mp4 |
91.39Мб |
| 8 - 00 Intro To Course And Python.mp4 |
57.22Мб |
| 81 - Source Files.html |
27б |
| 81 - SourceFiles.zip |
1.65Мб |
| 9 |
296.22Кб |
| 9 - 01 Variables.mp4 |
106.45Мб |
| TutsNode.net.txt |
63б |