automl

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

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

In-Database Machine Learning

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

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

AutoML library for deep learning

Automated Machine Learning with scikit-learn

An open source python library for automated feature engineering

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Google Brain AutoML

AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data

Differentiable architecture search for convolutional and recurrent networks

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

Fast and flexible AutoML with learning guarantees.

a delightful machine learning tool that allows you to train, test, and use models without writing code

Merlion: A Machine Learning Framework for Time Series Intelligence

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

A Hyperparameter Tuning Library for Keras

ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

Time Series Forecasting Best Practices & Examples