Mlr3tuningspaces

Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem
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Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
Nni13,66982721 days ago55September 14, 2023342mitPython
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Wandb7,9893962215 days ago266December 05, 20231,040mitPython
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Skypilot4,97542 months ago32October 29, 2023333apache-2.0Python
SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.
Determined2,71512 months ago221April 24, 2021142apache-2.0Go
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Scikit Optimize2,700801912 months ago19October 12, 2021320bsd-3-clausePython
Sequential model-based optimization with a `scipy.optimize` interface
Forecasting2,540
a year agomitPython
Time Series Forecasting Best Practices & Examples
Xcessiv1,232
16 years ago34August 21, 201722apache-2.0Python
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
Vizier1,14232 months ago35November 30, 202344apache-2.0Python
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Hyperparameter Optimization Of Machine Learning Algorithms1,025
2 years agomitJupyter Notebook
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
Onepanel6991a year ago64November 15, 202185apache-2.0Go
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
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