Hyperparameter Search Python Packages

ray

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

wandb

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

scikit-optimize

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

ant-ray-cpp-nightly

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

ray-cpp

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

smac

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

ant-ray-nightly

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

lale

Library for Semi-Automated Data Science

ant-ray

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

rl-zoo3

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

octis

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

sambo

🎯 📈 Sequential and Model-Based Optimization in Python, featuring SCE-UA, SMBO, and SHGO algorithms. SOTA perfomance; 0 deps.

pyrameter

Structure, sample, and savor hyperparameter searches.

wandb-ng

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

maggy

Distribution transparent Machine Learning experiments on Apache Spark

ve-ray

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

malet

Hyperparameter search and metric visualization tool for personal research.

neuraxle

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.

pygenetics

Genetic algorithm framework for tuning arbitrary functions

syftr

syftr is an agent optimizer that helps you find the best agentic workflows for your budget.

auto-surprise

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

parameter-sherpa

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

secretflow-ray

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

benderopt

Black-box optimization library