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

Automated Machine Learning with scikit-learn

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.

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

Time Series Forecasting Best Practices & Examples

Determined: Deep Learning Training Platform

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…

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

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

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

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

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

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

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.

EvalML is an AutoML library written in python.

Tuning hyperparams fast with Hyperband

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

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…

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