AutoML

A hyperparameter optimization framework

Fast and Accurate ML in 3 Lines of Code

An auto-evolution framework that optimizes anything — your 7×24 team of algorithm engineers.

Lightning ⚡️ fast forecasting with statistical and econometric models.

Scalable and user friendly neural :brain: forecasting algorithms.

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.

Distributed Asynchronous Hyperparameter Optimization in Python

AutoML library for deep learning

Hyper-parameter optimization for sklearn

Automated Machine Learning with scikit-learn

AI Infra / AI Orchestration / AI Control Plane

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Automatic architecture search and hyperparameter optimization for PyTorch

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Sequential model-based optimization with a `scipy.optimize` interface

Machine Learning in R

Hyperparameter Experiments with TensorFlow and Keras

MLBox is a powerful Automated Machine Learning python library.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.