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