143 Open source projects that are alternatives of or similar to CamelsOptimizer

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

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

a distributed Hyperband implementation on Steroids

A toolset for black-box hyperparameter optimisation.

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Python library for Bayesian hyper-parameters optimization

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

Bayesian Optimization using GPflow

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

Sequential Model-based Algorithm Configuration

A fully decentralized hyperparameter optimization framework

Toolbox for Bayesian Optimization and Model-Based Optimization in R

Automated Machine Learning with scikit-learn

Experimental Global Optimization Algorithm

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

Parallel Hyperparameter Tuning in Python

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

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

Simple, but essential Bayesian optimization package

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

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

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

Hyperparameter optimization in Julia.

PHYSBO -- optimization tools for PHYsics based on Bayesian Optimization

A shell-friendly hyperparameter search tool inspired by Optuna

A general-purpose pythonic genetic algorithm.

⚡️ AllenNLP plugin for adding subcommands to use Optuna, making hyperparameter optimization easy

Codebase for "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization", ICML 2018.

Bayesian Optimization algorithms with various recent improvements

Python library for CMA Evolution Strategy.

Mixed-Integer Parallel Efficient Global Optimization

Examples for https://github.com/optuna/optuna

Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.

Set model hyperparameters using deterministic, exact algorithms.

Fitness landscape exploration sandbox for biological sequence design.

Machine Learning Tool Box

Polyaxon Core Client & CLI to streamline MLOps

Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.

Real-time Web Dashboard for Optuna.

Scalable, structured, dynamically-scheduled hyperparameter optimization.

MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

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

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Hyperparameter optimization package of the mlr3 ecosystem

Your local Flux surgeon

Generalized and Efficient Blackbox Optimization System.

Bayesian Optimization and Grid Search for xgboost/lightgbm

Black box hyperparameter optimization made easy.

A library for doing Bayesian Optimization using Gaussian Processes (blackbox optimizer) in Go/Golang.

ICML'2022: Black-Box Tuning for Language-Model-as-a-Service

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

A scikit-learn compatible implementation of hyperband

Tutorial on Bayesian optimization in R

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

A Python package for approximate Bayesian inference and optimization using Gaussian processes

🦅Hyperparameter optimization for machine learning pipelines 🦅

A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.

pyrff: Python implementation of random fourier feature approximations for gaussian processes

A Clojure machine learning library

A simple collection of well working NLP models (Keras, H2O, StarSpace) tuned and benchmarked on a variety of datasets.