recommender-systems.md

Recommender Systems

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

Evaluating Recommender Systems

1. An exhaustive list of methods to evaluate
2. Choosing the best for your business
3. Evaluating
4. survey of accuracy eval metrics for RS by Microsoft
5. Building a validation framework
6. Evaluation Metrics for RS
7. offline vs online validation
8. Evaluating RS

TOOLS

1. Surprise, docs,
2. Grover prince , related article
3. Recsys git