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  • Evaluating Recommender Systems
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  1. Machine Learning

Recommender Systems

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Last updated 2 years ago

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  1. vidhya

  3. , validating using imdb data, git

  4. ,

  5. , a serious review of algorithms

  9. Medium on Movies

    1. Part 1

    2. using open ai

  10. Medium series on collaborative filtering and embeddings , ,

  11. on kaggle

  16. high sparsity

  18. Excel & fastai,

Evaluating Recommender Systems

TOOLS

, ,

,

git

Beginner guide
Real python on CF
Intro to, using item-item or user-item
Tfidf cosine similarity
countvec cosine
Various implementations of CF
Collaborative filtering, SVD
Part1,
Spotlight, item2vec, Neural nets for Recommender systems
A general tutorial, has a nice intro
matrix factorization in movies, users vs movies.
Part 2 using collaborative filtering
Part 3 using col-filtering with neural nets
Part 1
part 2
git
Movie recommender systems
On git
Matrix factorization
Collaborative filtering with binary countvec data, item-item, didnt work well on another domain
Netflix competition, matrix factorization over classical algorithms, a survey paper
Movie similarity based on genre
Similar entities, matrix multiplication
Euclidean distance with high sparse data
git
CF for movie recommendation
Comparison item vs user cf
build a recommendation engine with collaborative filtering
An exhaustive list of methods to evaluate
Choosing the best for your business
Evaluating
survey of accuracy eval metrics for RS by Microsoft
Building a validation framework
Evaluation Metrics for RS
offline vs online validation
Evaluating RS
Surprise
docs
Grover prince
related article
Recsys