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

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, 17+ clouds, or on-prem).

Automated Machine Learning with scikit-learn

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

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Automated Machine Learning on Kubernetes

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.

EvalML is an AutoML library written in python.

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps enviro…

Tuning hyperparams fast with Hyperband

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

Library for Semi-Automated Data Science

Library for automatic retraining and continual learning