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, 20+ clouds, or on-prem).

Automated Machine Learning with scikit-learn

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…

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

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.

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

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.

HyperView is a terminal-first TradingView strategy lab for downloading market data, backtesting Python strategies with Pine-like behavior, and optimizing SL/TP parameters.

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)

The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.

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

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning