The Top 58 Hyperparameter Optimization Open Source Projects

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The Top 58 Hyperparameter Optimization Open Source Projects

Categories > Machine Learning > Hyperparameter Optimization

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

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.

Auto Sklearn ⭐ 5,253

Automated Machine Learning with scikit-learn

Optuna ⭐ 4,194

A hyperparameter optimization framework

Autogluon ⭐ 3,020

AutoGluon: AutoML for Text, Image, and Tabular Data

Awesome Automl Papers ⭐ 2,858

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

Hyperas ⭐ 2,080

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Auto_ml ⭐ 1,523

[UNMAINTAINED] Automated machine learning for analytics & production

Talos ⭐ 1,381

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Xcessiv ⭐ 1,254

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

Determined ⭐ 1,158

Determined: Deep Learning Training Platform

Mljar Supervised ⭐ 935

Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

Rl Baselines Zoo ⭐ 821

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Awesome Automl And Lightweight Models ⭐ 685

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

Test Tube ⭐ 661

Python library to easily log experiments and parallelize hyperparameter search for neural networks

Gradient Free Optimizers ⭐ 650

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical search spaces.

Hyperparameter_hunter ⭐ 648

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Sequential Model-based Algorithm Configuration

Hyperband ⭐ 556

Tuning hyperparams fast with Hyperband

Auto Tune Models - A multi-tenant, multi-data system for automated machine learning (model selection and tuning).

Hyperparameter Optimization Of Machine Learning Algorithms ⭐ 500

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Hpbandster ⭐ 454

a distributed Hyperband implementation on Steroids

Experimental Global Optimization Algorithm

Neuraxle ⭐ 376

A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

Hypersearch ⭐ 374

Hyperparameter optimization for PyTorch.

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Awesome Distributed Deep Learning ⭐ 274

A curated list of awesome Distributed Deep Learning resources.

My Data Competition Experience ⭐ 267

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

Bayesian Optimization ⭐ 242

Python code for bayesian optimization using Gaussian processes

Gpflowopt ⭐ 229

Bayesian Optimization using GPflow

Cornell Moe ⭐ 198

A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

Library for Semi-Automated Data Science

Asynchronous Distributed Hyperparameter Optimization.

Toolbox for Bayesian Optimization and Model-Based Optimization in R

Coursera Deep Learning Specialization ⭐ 171

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Auptimizer ⭐ 162

An automatic ML model optimization tool.

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

A simple, extensible library for developing AutoML systems

Hyperactive ⭐ 146

A hyperparameter optimization and meta-learning toolbox for convenient and fast prototyping of machine-/deep-learning models.

Mlmodels ⭐ 145

mlmodels : Machine Learning and Deep Learning Model ZOO for Pytorch, Tensorflow, Keras, Gluon models...

Deep_architect_legacy ⭐ 144

DeepArchitect: Automatically Designing and Training Deep Architectures

Time Series Cross-Validation -- an extension for scikit-learn

Rl Baselines3 Zoo ⭐ 143

A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included.

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

Population Based Training (in PyTorch with sqlite3). Status: Unsupported

Automl_alex ⭐ 125

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

Deeplearning Notes ⭐ 121

Notes for Deep Learning Specialization Courses led by Andrew Ng.

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

Hypertunity ⭐ 119

A toolset for black-box hyperparameter optimisation.

Chocolate ⭐ 113

A fully decentralized hyperparameter optimization framework

Deephyper ⭐ 113

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

Deep_architect ⭐ 109

A general, modular, and programmable architecture search framework

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

Hyperopt Keras Cnn Cifar 100 ⭐ 96

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

Purely functional genetic algorithms for multi-objective optimisation

Simple, but essential Bayesian optimization package

Deep_traffic ⭐ 47

MIT DeepTraffic top 2% solution (75.01 mph) 🚗.

1-58 of 58 projects

Advertising 📦 10

Application Programming Interfaces 📦 124

Applications 📦 192

Artificial Intelligence 📦 78

Blockchain 📦 73

Build Tools 📦 113

Cloud Computing 📦 80

Code Quality 📦 28

Collaboration 📦 32

Command Line Interface 📦 49

Community 📦 83

Companies 📦 60

Compilers 📦 63

Computer Science 📦 80

Configuration Management 📦 42

Content Management 📦 175

Control Flow 📦 213

Data Formats 📦 78

Data Processing 📦 276

Data Storage 📦 135

Economics 📦 64

Frameworks 📦 215

Graphics 📦 110

Hardware 📦 152

Integrated Development Environments 📦 49

Learning Resources 📦 166

Libraries 📦 129

Lists Of Projects 📦 22

Machine Learning 📦 347

Mapping 📦 64

Marketing 📦 15

Mathematics 📦 55

Messaging 📦 98

Networking 📦 315

Operating Systems 📦 89

Operations 📦 121

Package Managers 📦 55

Programming Languages 📦 245

Runtime Environments 📦 100

Science 📦 42

Security 📦 396

Social Media 📦 27

Software Architecture 📦 72

Software Development 📦 72

Software Performance 📦 58

Software Quality 📦 133

Text Editors 📦 49

Text Processing 📦 136

User Interface 📦 330

User Interface Components 📦 514

Version Control 📦 30

Virtualization 📦 71

Web Browsers 📦 42

Web Servers 📦 26

Web User Interface 📦 210