A collection of differentiable SVD methods and ICCV21 "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"

Differentiable matrix factorizations using ImplicitDifferentiation.jl.

Designed a movie recommendation system using content-based, collaborative filtering based, SVD and popularity based approach.

Recommend movies to users by RBMs, TruncatedSVD, Stochastic SVD and Variational Inference

Includes the SVD-based approximation algorithms for compressing deep learning models and the FPGA accelerators exploiting such approximation mechanism, as described in the paper Mapping multiple LSTM models on FPGAs.

Projet d'étude système de recommendation en utilisant filtrage collaboratif

This repo contains a machine learning model made using advanced and enhanced algos like KNN,SVD and also concepts like vectorization ,cosine similarity which predicts the similar movies for a given fav movie of user. So no more time wasting on searching for a good of you're choice

CVM Class Library

Применяем Singular Value Decomposition with implicit feedback для задачи рекомендации аниме

Coursework for CS550 : Massive Data Mining. Topics covered include Map-Reduce, Association Rules, Frequent Itemsets, Locality-Sensitive Hashing (LSH), Singular Value Decomposition (SVD), Page Rank, k-means, Modularity, Spectral Clustering, Clique-based communities, Clustering Data Streams.

Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity

This project demonstrates the application of Singular Value Decomposition (SVD) for image compression using Python and NumPy.

Code of Book Recommendation System, suggests books to users based on their interests and reading history along with the content of the item.

Movie recommendation system based on popularity and also using KNN and Cosine similarity. 🎥🍿

Toy example of a tool to optimize CNN layers widths, according their SVD decomposition

Building a Collaborative Filtering based Recommender system using e-commerce data.

Sparse Truncated SVD Benchmark (Python)

Books recommendation system by collaborative filtering and certain visualization are done on data.

redsvd - RandomizED Singular Value Decomposition

In this project we are comparing two approaches for movie recommendation for a new user or existing user based on their age, gender, occupation.