Spearmint

Spearmint

Bayesian optimization for efficient machine learning experiments.

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About Spearmint

Spearmint is a Python-based open-source software package for performing Bayesian optimization, primarily aimed at automating and optimizing machine learning experiments. It is particularly suited for academic researchers and practitioners who wish to minimize experimental runs while tuning parameters to reach optimal results. Spearmint supports advanced features such as multi-task optimization, input warping, and handling unknown constraints, and outputs results for direct analysis or database access.

Resources

Product Website

Visit Spearmint's official website for product details and getting started.

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Documentation

Comprehensive guide and API reference for using Spearmint for Bayesian optimization.

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Community Discussions

Engage with other users and developers, share experiences, and ask questions about Spearmint.

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Examples and Tutorials

A collection of examples and tutorials to get started with Spearmint and understand its capabilities.

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