Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Nni | 13,725 | 8 | 27 | a month ago | 55 | September 14, 2023 | 342 | mit | Python | |
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. | ||||||||||
Autokeras | 9,023 | 7 | 5 | 4 months ago | 58 | January 28, 2023 | 132 | apache-2.0 | Python | |
AutoML library for deep learning | ||||||||||
Autogluon | 7,027 | 14 | 14 days ago | 1,168 | December 10, 2023 | 299 | apache-2.0 | Python | ||
AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data | ||||||||||
Flaml | 3,500 | 11 | 3 months ago | 92 | October 02, 2023 | 210 | mit | Jupyter Notebook | ||
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP. | ||||||||||
Auto_ml | 1,442 | 1 | 6 | 5 years ago | 78 | February 22, 2018 | 182 | mit | Python | |
[UNMAINTAINED] Automated machine learning for analytics & production | ||||||||||
Mlbox | 1,403 | a year ago | 21 | August 25, 2020 | 26 | other | Python | |||
MLBox is a powerful Automated Machine Learning python library. | ||||||||||
Fast Autoaugment | 1,358 | 3 years ago | 22 | mit | Python | |||||
Official Implementation of 'Fast AutoAugment' in PyTorch. | ||||||||||
Autodl | 999 | 2 years ago | 2 | May 18, 2020 | 23 | apache-2.0 | Python | |||
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS. | ||||||||||
Hyperactive | 475 | 5 | 4 months ago | 75 | October 24, 2023 | 8 | mit | Python | ||
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. | ||||||||||
Automl Implementation For Static And Dynamic Data Analytics | 443 | 10 months ago | mit | Jupyter Notebook | ||||||
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning |