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Machine & Deep Learning Compendium
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Recommender Systems

  1. 1.
    ​Beginner guide vidhya
  2. 2.
    ​Real python on CF​
  3. 3.
    ​Intro to, using item-item or user-item, validating using imdb data, git
  4. 4.
    ​Tfidf cosine similarity, countvec cosine​
  5. 5.
    ​Various implementations of CF, a serious review of algorithms
  6. 6.
    ​Collaborative filtering, SVD​
  7. 7.
    ​Part1, Spotlight, item2vec, Neural nets for Recommender systems​
  8. 8.
    ​A general tutorial, has a nice intro​
  9. 9.
    Medium on Movies
    1. 1.
      Part 1 matrix factorization in movies, users vs movies.​ ​
    2. 2.
      ​Part 2 using collaborative filtering using open ai
    3. 3.
      ​Part 3 using col-filtering with neural nets​
  10. 10.
    Medium series on collaborative filtering and embeddings Part 1, part 2, git​
  11. 11.
    ​Movie recommender systems on kaggle
    1. 1.
      ​On git​
  12. 12.
    ​Matrix factorization ​
  13. 13.
    ​Collaborative filtering with binary countvec data, item-item, didnt work well on another domain​
  14. 14.
    ​Netflix competition, matrix factorization over classical algorithms, a survey paper​
  15. 15.
    ​Movie similarity based on genre ​
  16. 16.
    ​Similar entities, matrix multiplication high sparsity
  17. 17.
    ​Euclidean distance with high sparse data​
  18. 18.
    Excel & fastai, git​
  19. 19.
    ​CF for movie recommendation​
  20. 20.
    ​Comparison item vs user cf​

TOOLS

​Recsys git
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