There are 44 repositories under automated-machine-learning topic.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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
AutoGluon: AutoML for Image, Text, and Tabular Data
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
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
A fast library for AutoML and tuning.
[UNMAINTAINED] Automated machine learning for analytics & production
Official Implementation of 'Fast AutoAugment' in PyTorch.
MLBox is a powerful Automated Machine Learning python library.
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Sequential Model-based Algorithm Configuration
a distributed Hyperband implementation on Steroids
Efficient Learning of Augmentation Policy Schedules
[UNMAINTAINED] Automated machine learning- just give it a data file! Check out the production-ready version of this project at ClimbsRocks/auto_ml
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
Automated modeling and machine learning framework FEDOT
Archai accelerates Neural Architecture Search (NAS) through fast, reproducible and modular research.
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Library for Semi-Automated Data Science
R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, recommenders, and EDA.
An automatic ML model optimization tool.
A specially designed light version of Fast AutoAugment
AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
:chart: SIMON is powerful, flexible, open-source and easy to use machine learning knowledge discovery platform :computer:
[ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Fully automated code for Covid-19 detection from CT scans from paper: https://doi.org/10.1016/j.bspc.2021.102588
collecting related resources of automated machine learning here
Codebase for "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization", ICML 2018.
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.