Top 103 hyperparameter-optimization open source projects

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

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

Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models

Automated modeling and machine learning framework FEDOT

A library for performing hyperparameter optimization

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define m…

Easy Hyper Parameter Optimization with mlr and mlrMBO.

Yes, it's a camel case.

Python library for Bayesian hyper-parameters optimization

Hyperparameter optimization in Julia.

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

Black box hyperparameter optimization made easy.

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

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

Python library for CMA Evolution Strategy.

MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

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

🦅Hyperparameter optimization for machine learning pipelines 🦅

Autonomous Performance Tuning for Kubernetes !

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

A shell-friendly hyperparameter search tool inspired by Optuna

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

Machine Learning Tool Box

Your local Flux surgeon

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

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

PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).

Streamlined machine learning experiment management.

Using Kafka-Python to illustrate a ML production pipeline

Distribution transparent Machine Learning experiments on Apache Spark

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

A general-purpose pythonic genetic algorithm.

Set model hyperparameters using deterministic, exact algorithms.

Polyaxon Core Client & CLI to streamline MLOps

Real-time Web Dashboard for Optuna.

Parallel Hyperparameter Tuning in Python

Scalable, structured, dynamically-scheduled hyperparameter optimization.

Hyperparameter optimization package of the mlr3 ecosystem

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

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

A scikit-learn compatible implementation of hyperband

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

A Clojure machine learning library