A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

AutoML library for deep learning

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

An open source python library for automated feature engineering

Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Automated Machine Learning with scikit-learn

Fast and flexible AutoML with learning guarantees.

Google Brain AutoML

Differentiable architecture search for convolutional and recurrent networks

Machine Learning in one line of code

A curated list of automated machine learning papers, articles, tutorials, slides and projects

AutoGluon: AutoML Toolkit for Deep Learning

An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

Provide an input CSV and a target field to predict, generate a model + code to run it.

[UNMAINTAINED] Automated machine learning for analytics & production

Time Series Forecasting Best Practices & Examples

A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.

Open-source implementation of Google Vizier for hyper parameters tuning

Java and Kotlin Code samples used on cloud.google.com

MLBox is a powerful Automated Machine Learning python library.

[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

Official Implementation of 'Fast AutoAugment' in PyTorch.

Automated deep learning algorithms implemented in PyTorch.

A curated list of research in machine learning system. I also summarize some papers if I think they are really interesting.

Genetic neural architecture search with Keras

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Otto makes machine learning an intuitive, natural language experience.🏆 Facebook AI Challenge winner ⭐️ #4 Trending JS Project on GitHub ⭐️ #15 Trending (All Languages)

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment