204 Open source projects that are alternatives of or similar to Sherpa

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

Sequential Model-based Algorithm Configuration

Automated Machine Learning with scikit-learn

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Parallel Hyperparameter Tuning in Python

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

Sequential model-based optimization with a `scipy.optimize` interface

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

This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"

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

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.

a distributed Hyperband implementation on Steroids

Generalized and Efficient Blackbox Optimization System.

A scikit-learn compatible implementation of hyperband

A library for performing hyperparameter optimization

Experimental Global Optimization Algorithm

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

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

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

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

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

Simple, but essential Bayesian optimization package

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

A fully decentralized hyperparameter optimization framework

Machine Learning Tool Box

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

Python library for Bayesian hyper-parameters optimization

[UNMAINTAINED] Automated machine learning for analytics & production

Bayesian Optimization and Grid Search for xgboost/lightgbm

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

A modular active learning framework for Python

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

Toolbox for Bayesian Optimization and Model-Based Optimization in R

An automatic ML model optimization tool.

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

Library for Semi-Automated Data Science

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

Tuning hyperparams fast with Hyperband

Determined: Deep Learning Training Platform

Purely functional genetic algorithms for multi-objective optimisation

Hyperparameter optimization in Julia.

Hyperparameter optimization package of the mlr3 ecosystem

A general-purpose pythonic genetic algorithm.

Yes, it's a camel case.

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

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

A toolset for black-box hyperparameter optimisation.

Bayesian Optimization using GPflow

Distribution transparent Machine Learning experiments on Apache Spark

Black box hyperparameter optimization made easy.

Generalized and Efficient Blackbox Optimization System [SIGKDD'21].

books and courses on machine learning

🚀 A demonstration of hyperparameter optimization using Optuna for models implemented with AllenNLP.

ytopt: machine-learning-based search methods for autotuning

Implementation of Stochastic Gradient MCMC algorithms

Python library for CMA Evolution Strategy.

Data System for Optimized Deep Learning Model Selection

Examples how MLJAR can be used

Fitness landscape exploration sandbox for biological sequence design.

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