Popular GitHub Repositories for Random Matrix Theory

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

A Python scikit for building and analyzing recommender systems

Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

Cross-platform chatbot framework made with love

A Python implementation of LightFM, a hybrid recommendation algorithm.

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Fast and flexible AutoML with learning guarantees.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

A python library for decision tree visualization and model interpretation.

Deep recommender models using PyTorch.

A distributed graph deep learning framework.

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

A collection of research papers on decision, classification and regression trees with implementations.

Datasets, tools, and benchmarks for representation learning of code.

High-efficiency floating-point neural network inference operators for mobile, server, and Web

Recommender Learning with Tensorflow2.x