R package for integrating and analyzing multiple single-cell datasets

Nonnegative matrix factorizations using CUDA

seqArchR: Identifying (promoter) sequence architectures de novo using NMF

SNMF: Integrated Learning of Mutational Signatures and Prediction of DNA Repair Deficiencies by Goossens S, Tepeli YI, Gonçalves JP

This notebook analyzes Spotify song data and builds a recommendation system to suggest songs based on user listening behavior.

Filtering drums out of music using matrix factorization and CNN ML Model

Clustering and resource allocation using Deterministic Annealing Approach and Orthogonal Non-negative Matrix Factorization O-(NMF)

My Programming Assignments from the MA 544 Numerical Linear Algebra for Big Data Course from Stevens Institute of Technology

A promising Spotify Wrapped feature using Principal Component Analysis

Solve many kinds of least-squares and matrix-recovery problems

This project showcases an end-to-end workflow for topic modeling and text analysis using a variety of machine learning and natural language processing techniques. The goal of this project is to extract meaningful topics from a collection of text documents, enabling insights, categorization, and understanding of the underlying themes in the data.

Python Distributed Non Negative Matrix Factorization with custom clustering

Similarity Weighted Nonnegative Embedding (SWNE), a method for visualizing high dimensional datasets

A pytorch package for non-negative matrix factorization.

Nonnegative matrix factorization

A Natural Language Processing Project: Use NewsAPI to gather URL's of news articles, along with webscraping, gather news articles and generate a bias classifier to then run on news sources that are considered "centered" by AllSides Media to determine the validity of that classification.

NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1

Self-supervised semi-supervised nonnegative matrix factorization for data clustering

Elastic Adversarial Deep Nonnegative Matrix Factorization for Matrix Completion

Face Recognition with SVM classifier using PCA, ICA, NMF, LDA reduced face vectors