Python hyperparameter-optimization

Open-source Python projects categorized as hyperparameter-optimization | Edit details

Top 23 Python hyperparameter-optimization Projects

  • Ray

    An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

    Project mention: Is it normal to have a negative and near-zero explained variance in PPO? | | 2021-12-25

    I guess I did, as I directly use the PPO agent provided by the RLlib.

  • nni

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

    Project mention: Automated Machine Learning (AutoML) - 9 Different Ways with Microsoft AI | | 2021-10-04

    For a complete tutorial, navigate to this Jupyter Notebook:

  • OPS

    OPS - Build and Run Open Source Unikernels. Quickly and easily build and deploy open source unikernels in tens of seconds. Deploy in any language to any cloud.

  • auto-sklearn

    Automated Machine Learning with scikit-learn

    Project mention: Why not AutoML every tabular data? | | 2021-07-26

    Efficiency Ignoring the feature engineering aspects aside, a typical data scientist workflow involves trying out the different models. Some of the AutoML modules like H2O AutoML, AutoSklearn does this for you, and allow you to interpret your models. All these save so much time experimenting with the standard models.

  • optuna

    A hyperparameter optimization framework

    Project mention: Trading Algos - 5 Key Metrics and How to Implement Them in Python | | 2022-01-08

    Nothing can beat iteration and rapid optimization. Try running things like grid experiments, batch optimizations, and parameter searches. Take a look at various packages like hyperopt or optuna as packages that might be able to help you here!

  • autogluon

    AutoGluon: AutoML for Text, Image, and Tabular Data

    Project mention: What will the data science job market be like in 5 years? | | 2021-08-14

    Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.

  • mljar-supervised

    Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

    Project mention: I'm Looking to Help Contribute, I am very confident with my skills | | 2021-12-02

    Automated Machine Learning (AutoML) Python package You can check list of open issues. Or I can recommend some just tell me your preferences (Im the main contributor)

  • determined

    Determined: Deep Learning Training Platform

    Project mention: How to train large deep learning models as a startup | | 2021-10-07

    Check out Determined to help manage this kind of work at scale: Determined leverages Horovod under the hood, automatically manages cloud resources and can get you up on spot instances, T4's, etc. and will work on your local cluster as well. Gives you additional features like experiment management, scheduling, profiling, model registry, advanced hyperparameter tuning, etc.

    Full disclosure: I'm a founder of the project.

  • SonarQube

    Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.

  • Hypernets

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

    Project mention: [N][R] A Brief Tutorial for Developing AutoML Tools with Hypernets | | 2021-06-28

    Please see here for the Hypernets library.

  • rl-baselines-zoo

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

    Project mention: How do I convert zoo / gym trained models to TensorFlow Lite or PyTorch TorchScript? | | 2021-03-22 (TensorFlow based, using

  • Gradient-Free-Optimizers

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

    Project mention: Gradient-Free-Optimizers A collection of modern optimization methods in Python | | 2021-02-28
  • rl-baselines3-zoo

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

    Project mention: Easily load and upload Stable-baselines3 models from the Hugging Face Hub 🤗 | | 2022-01-21

    Integrating RL-baselines3-zoo

  • Hyperactive

    An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

    Project mention: Hyperactive: An optimization and data collection toolbox for AutoML | | 2021-05-15

    Automated modeling and machine learning framework FEDOT

    Project mention: Winning a Flood-Forecasting Hackathon with Hydrology and AutoML | | 2022-01-14

    Hi to everyone! I am a developer of the FEDOT framework, and our team and I (NSS_lab team) recently won a hackathon EmergencyDataHack (rus). There was a recent post on TowardsDataSciense based on our competition things: Winning a Flood-Forecasting Hackathon with Hydrology and AutoML.


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

    Project mention: (NLP) Best practices for topic modeling and generating interesting topics? | | 2021-05-31

    My team and I have recently released a python library called OCTIS ( that allows you to automatically optimize the hyperparameters of a topic model according to a given evaluation metric (not log-likelihood). I guess, in your case, you might be interested in topic coherence. So you will get good quality topics with a low effort on the choice of the hyperparameters. Also, we included some state-of-the-art topic models, e.g. contextualized topic models (

  • GPflowOpt

    Bayesian Optimization using GPflow

    Project mention: [D] Choosing best parameters from an optimization | | 2021-06-05

    1- Hyperparameter optimization as already suggested by u/sener87 but I think your validation does not have to be change as it tests generalization as far as I understand you right. If you have more parameter/larger search space, you may look into Bayesian optimization for this task as implemented e.g. with tensorflow, torch or numpy frameworks.

  • orion

    Asynchronous Distributed Hyperparameter Optimization. (by Epistimio)

    Project mention: Git token, how to I encourage git to have me put in a username and password? | | 2021-09-01

    $ git remote show origin [email protected]:Epistimio/orion.git << SSH $ git remote show origin << HTTPs

  • TSCV

    Time Series Cross-Validation -- an extension for scikit-learn

    Project mention: [P] First release candidate of tscv v0.0.5 | | 2021-03-19

    The wheel binary can be downloaded from my GitHub repo for early testing. If you notice any bug, please open a ticket in the repo. The final version is expected to be released by the end of this month, and users will be able to pip install it.

  • optuna-examples

    Examples for

    Project mention: Data Scientists are dying out | | 2022-01-18

    That's still regular ML because you are in charge of the features. Optuna might make your life easier though:

  • Sklearn-genetic-opt

    Hyperparameters tuning and feature selection, using evolutionary algorithms.

    Project mention: GitHub - rodrigo-arenas/Sklearn-genetic-opt: Hyperparameters tuning and feature selection, using evolutionary algorithms. | | 2021-12-19
  • tuneta

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

    Project mention: Klines/candles: What's the real difference between long intervals and short intervals? | | 2021-10-18

    You can try which uses a clustered center for parameter selection to avoid peaks and can also constrain to time ranges


    Python Automated Machine Learning library for tabular data.

    Project mention: Introducing my AutoML library | | 2021-06-18

    I'm excited to introduce you my (and another great developer) school diploma project. Fully open-source, Automated Machine Learning Library! We are beating built-in AutoML in SAP famous product. GitHub repository (waiting for your stars): Web-application for users who don't want to code:

  • ds2ai

    The MLOps platform for innovators 🚀

    Project mention: Release: End-to-End MLOps Platform | | 2021-07-13
  • easyopt

    zero-code hyperparameters optimization framework

    Project mention: Easyopt: Zero-Code Hyperparameter Optimization | | 2021-09-16
NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2022-01-21.

Python hyperparameter-optimization related posts


What are some of the best open-source hyperparameter-optimization projects in Python? This list will help you:

Project Stars
1 Ray 18,966
2 nni 10,884
3 auto-sklearn 5,992
4 optuna 5,848
5 autogluon 4,071
6 mljar-supervised 1,755
7 determined 1,608
8 Hypernets 1,037
9 rl-baselines-zoo 961
10 Gradient-Free-Optimizers 834
11 rl-baselines3-zoo 515
12 Hyperactive 357
13 FEDOT 293
14 OCTIS 283
15 GPflowOpt 241
16 orion 215
17 TSCV 163
18 optuna-examples 139
19 Sklearn-genetic-opt 83
20 tuneta 67
21 SAP-HANA-AutoML 46
22 ds2ai 8
23 easyopt 8
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