[FTUForum.com] [UDEMY] Python Machine Learning Basics Shallow Learning Algorithms [FTU]

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文档列表

2. Machine Learning Framework/4. MI Python skeleton.mp4 61.5 MB
3. SVD/1. SVD implementation.mp4 55.6 MB
5. Going Live/3. Surpriselib and Flask.mp4 50.9 MB
2. Machine Learning Framework/1. Scikit Surprise.mp4 40.4 MB
4. KNN/1. KNN implementation.mp4 39.5 MB
3. SVD/2. SVD Theory.mp4 38.8 MB
5. Going Live/1. Display KNN neighbors.mp4 33.2 MB
1. Introduction/1. What is Machine Learning.mp4 30.1 MB
4. KNN/2. Knn theory.mp4 23.7 MB
5. Going Live/2. Display SVD Item Predictions.mp4 23.7 MB
2. Machine Learning Framework/2. Evaluation.mp4 22.6 MB
4. KNN/3. User vs Item.mp4 19.5 MB
1. Introduction/2. Shallow vs Deep learning.mp4 13.9 MB
1. Introduction/3. Theory vs Practice.mp4 12.0 MB
2. Machine Learning Framework/3. Install Python 3.5+.mp4 7.7 MB
2. Machine Learning Framework/4. MI Python skeleton.vtt 9.1 kB
2. Machine Learning Framework/2. Evaluation.vtt 8.1 kB
3. SVD/1. SVD implementation.vtt 7.0 kB
5. Going Live/3. Surpriselib and Flask.vtt 6.3 kB
1. Introduction/1. What is Machine Learning.vtt 5.9 kB
4. KNN/2. Knn theory.vtt 5.7 kB
3. SVD/2. SVD Theory.vtt 4.7 kB
2. Machine Learning Framework/1. Scikit Surprise.vtt 4.5 kB
4. KNN/1. KNN implementation.vtt 4.3 kB
5. Going Live/1. Display KNN neighbors.vtt 4.2 kB
5. Going Live/2. Display SVD Item Predictions.vtt 3.9 kB
1. Introduction/3. Theory vs Practice.vtt 3.7 kB
1. Introduction/2. Shallow vs Deep learning.vtt 3.4 kB
4. KNN/3. User vs Item.vtt 2.4 kB
2. Machine Learning Framework/3. Install Python 3.5+.vtt 1.0 kB
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0. Websites you may like/How you can help Team-FTU.txt 237 Bytes
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3. SVD/3. Implement SVD().html 150 Bytes
4. KNN/4. Implementing KNN.html 150 Bytes
3. SVD/2.1 Singular Value Decomposition Stanford University.html 104 Bytes