A website for recommending books
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Updated
Dec 17, 2019 - Python
A website for recommending books
Perform Sparse Matrix Factorization using GPU in CUDA
Compressing RGB images using SVD matrix decomposition
Global optimization for mixed membership matrix factorization for omics data. Code for Zhang, et al, 2019
Applied linear Algebra Projects -Spring 2022
Hybrid (content-based/collaborative) recommendation model to find the best movie for two people to watch together.
A recommender system using matrix factorization algorithm and MovieLens dataset.
Simple and user-friendly Python package for building recommendation systems based on PMF.
Load Tensor Decompositions results
Recommender System
A prior learning and sampling model informed tool for learning with Single Cell RNA-Seq data
Autoencoding Topographic Factors
Articles recommendation engine for IBM Watson Studio platform
Matrix ADT for linear algebra applications.
Ressources usage optimisation, memory and calculation... using Cuthill Mac-Kee algorithm. Afterward, optimised matrix is solved with LDLT factorization.
I built recommender systems for recommending products to user using Model-based recommendation system.
Matrix factorization is a class of collaborative filtering algorithms used in recommender systems. Matrix factorization algorithms work by decomposing the user-item interaction matrix into the product of two lower dimensionality rectangular matrices.
Text summarization based on SVD & NMF
Finds the L factor for a given mxn matrix.
This is a repository which save the soure code of the term project of ADS.
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