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28 search results found

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

Auto Sklearn ⭐ 7,262

Automated Machine Learning with scikit-learn

Forecasting ⭐ 2,540

Time Series Forecasting Best Practices & Examples

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

EvalML is an AutoML library written in python.

Neuraxle ⭐ 533

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 environments.

Tune Sklearn ⭐ 461

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

Agilerl ⭐ 457

Streamlining reinforcement learning with RLOps

Automl Implementation For Static And Dynamic Data Analytics ⭐ 443

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

Library for Semi-Automated Data Science

Hypernets ⭐ 256

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Auptimizer ⭐ 195

An automatic ML model optimization tool.

Automl_alex ⭐ 171

State-of-the art Automated Machine Learning python library for Tabular Data

Adatune ⭐ 144

Gradient based Hyperparameter Tuning library in PyTorch

PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms

Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

Distribution transparent Machine Learning experiments on Apache Spark

Mlprimitives ⭐ 67

Primitives for machine learning and data science.

Mindware ⭐ 54

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Auto Surprise ⭐ 25

An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀

Flexible Bayesian Optimization in R

Mlr3hyperband ⭐ 17

Successive Halving and Hyperband in the mlr3 ecosystem

Hpbandster Sklearn ⭐ 15

A scikit-learn wrapper for HpBandSter hyper parameter search.

Awesome Auto Ml ⭐ 13

Awesome list of AutoML frameworks - curated by @oskar-j

Mlr3tuningspaces ⭐ 10

Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem

Volkstuner ⭐ 9

An easy to use hyperparameter tuner

Automl Resources ⭐ 8

A list of resources, papers, and articles on AutoML, Automatic Hyperparameter Tuning, and Neural Architecture Search.

Neurosymbolic Tinyml ⭐ 5

TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning

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Python Automl (402)

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