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test-ml

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Treat your machine learning models like any other software asset: properly test them and fail builds if they don't meet your desired performance.

$ cd docs && make clean && make html

Open then index.html in the newly created docs/_build folder and you're good to go.

Overview

This library enables you to easily test machine learning artifacts. Specify a set of target metric, and the rest is taken care of.

Note

Status: alpha. Active development, but breaking changes may come.

Features

  • Rich CLI capabilities that enable you to configure metrics, input data, performance cut-offs, and more
  • Small, statically typed codebase, and extensive docstrings
  • Public API enabling embedding this library in any build process
  • Easily extensible with custom loaders, runners, and metrics

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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