Nicolas Hug
Machine learning Phd, software engineer
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matrix factorization
PCA
SVD
surprise
recommender systems
pygbm
gradient boosting decision trees
#matrix factorization
Understanding matrix factorization for recommendation (part 1) - preliminary insights on PCA
Understanding matrix factorization for recommendation (part 2) - the model behind SVD
Understanding matrix factorization for recommendation (part 3) - SVD for recommendation
Understanding matrix factorization for recommendation (part 4) - algorithm implementation
#PCA
Understanding matrix factorization for recommendation (part 1) - preliminary insights on PCA
Understanding matrix factorization for recommendation (part 2) - the model behind SVD
Understanding matrix factorization for recommendation (part 3) - SVD for recommendation
Understanding matrix factorization for recommendation (part 4) - algorithm implementation
#SVD
Understanding matrix factorization for recommendation (part 1) - preliminary insights on PCA
Understanding matrix factorization for recommendation (part 2) - the model behind SVD
Understanding matrix factorization for recommendation (part 3) - SVD for recommendation
Understanding matrix factorization for recommendation (part 4) - algorithm implementation
#surprise
Surprise, a Python scikit for building and analyzing recommender systems
#recommender systems
Surprise, a Python scikit for building and analyzing recommender systems
#pygbm
Pygbm, a fast pure-Python implementation of Gradient Boosting Decision Trees
#gradient boosting decision trees
Pygbm, a fast pure-Python implementation of Gradient Boosting Decision Trees
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