Popular GitHub Repositories for Random Matrices

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.

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..

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

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.

A distributed graph deep learning framework.

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

Named Entity Recognition (LSTM + CRF) - Tensorflow

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Text Classification Algorithms: A Survey

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

A curated list of Best Artificial Intelligence Resources

PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

A curated list of gradient boosting research papers with implementations.

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

(Linear-chain) Conditional random field in PyTorch.

Python library to easily log experiments and parallelize hyperparameter search for neural networks