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

👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

Four word embedding models implemented in Python. Supporting arbitrary context features

H2Oai GPU Edition

Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang

A 100x faster SVD for PyTorch⚡️

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.

Book Recommendation System built for Book Lovers📖. Simply Rate ⭐ some books and get immediate recommendations🤩

Official code for "Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes", CVPR2022

Fast truncated singular value decompositions

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.

Randomized Dimension Reduction Library

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

Python code implementing the power method for Singular Value Decomposition

Randomized Matrix Decompositions using R

A repository for recording the machine learning code