There are 5 repositories under svd topic.
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
A Python scikit for building and analyzing recommender systems
LAPACK development repository
:crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA
Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang
Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username
stable-video-diffusion-webui, img to videos| 图片生成视频
Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
Official code for "Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes", CVPR2022
pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, IA Lab and SocVis Lab.
Python 3.6 下的推荐算法解析,尽量使用简单的语言剖析原理,相似度度量、协同过滤、矩阵分解等
Digital Image Watermarking Method Based on Hybrid DWT-HD-SVD Technique: Attacks, PSNR, SSIM, NC
A sparsity aware implementation of "Binarized Attributed Network Embedding" (ICDM 2018).
a repository for my curriculum project
Generate zig code from ATDF or SVD files for microcontrollers.
A recommendation system using tensorflow
A collection of differentiable SVD methods and ICCV21 "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).
Product Recommendation System is a machine learning-based project that provides personalized product recommendations to users based on their interaction history, similar users, and also the popularity of products.
An introduction to matrix factorization and PCA and SVD.