102 Open source projects that are alternatives of or similar to hone

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

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

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

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.

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

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

Automated Machine Learning with scikit-learn

Sequential Model-based Algorithm Configuration

Tuning hyperparams fast with Hyperband

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

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

A hyperparameter optimization framework

a distributed Hyperband implementation on Steroids

Experimental Global Optimization Algorithm

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.

Hyperparameter optimization for PyTorch.

AutoGluon: AutoML for Text, Image, and Tabular Data

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

A curated list of awesome Distributed Deep Learning resources.

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

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

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

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