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README.md

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# MLonCode Core Library
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[![Build Status](https://travis-ci.org/src-d/ml-core.svg)](https://travis-ci.org/src-d/ml-core)
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[![codecov](https://codecov.io/github/src-d/ml-core/coverage.svg)](https://codecov.io/gh/src-d/ml-core)
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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
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[![Travis build status](https://travis-ci.com/src-d/ml-core.svg)](https://travis-ci.com/src-d/ml-core)
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[![Code coverage](https://codecov.io/github/src-d/ml-core/coverage.svg)](https://codecov.io/github/src-d/ml-core)
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[![Read the Docs](https://img.shields.io/readthedocs/ml-core.svg)](https://readthedocs.org/projects/ml-core/)
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[![Docker build status](https://img.shields.io/docker/build/srcd/ml-corer.svg)](https://hub.docker.com/r/srcd/ml-core)
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[![PyPi package status](https://img.shields.io/pypi/v/srcd-ml-core.svg)](https://pypi.python.org/pypi/srcd-ml-core)
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![stability: alpha](https://svg-badge.appspot.com/badge/stability/alpha?color=f47142)
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[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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Library for machine learning on source code. Provides commonly used algorithms and tools
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to process the code-related data, such as: Babelfish's UASTs, plain code text, etc.
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This library is the foundation for [MLonCode](https://github.com/src-d/awesome-machine-learning-on-source-code) research and development.
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It contains commonly used algorithms and tools to process the code-related data, such as [Babelfish's UASTs](docs.sourced.tech/babelfish), plain code text and other.
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## Contributions
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...are welcome! See [CONTRIBUTING.md](docs/CONTRIBUTING.md) and [CODE\_OF\_CONDUCT.md](docs/CODE_OF_CONDUCT.md).
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## License
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[Apache 2.0](LICENSE.md)
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## Glossary
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See [here](docs/GLOSSARY.md).

SUMMARY.md

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# CONTRIBUTING
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ml-core project is [Apache licensed](license.md) and accepts contributions via GitHub pull
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ml-core project is [Apache licensed](LICENSE.md) and accepts contributions via GitHub pull
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requests. This document outlines some of the conventions on development workflow, commit message formatting, contact points, and other resources to make it easier to get your contribution accepted.
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## Certificate of Origin
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The official support channels, for both users and contributors, are:
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* GitHub [issues](https://github.com/src-d/ml/issues)\*
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* GitHub [issues](https://github.com/src-d/ml-core/issues)\*
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* Slack: \#machine-learning room in the [source{d} Slack](https://join.slack.com/t/sourced-community/shared_invite/enQtMjc4Njk5MzEyNzM2LTFjNzY4NjEwZGEwMzRiNTM4MzRlMzQ4MmIzZjkwZmZlM2NjODUxZmJjNDI1OTcxNDAyMmZlNmFjODZlNTg0YWM)
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\*Before opening a new issue or submitting a new pull request, it's helpful to search the project - it's likely that another user has already reported the issue you're facing, or it's a known issue that we're already aware of.
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* The code is formatted according to [![PEP8](https://img.shields.io/badge/code%20style-pep8-orange.svg)](https://www.python.org/dev/peps/pep-0008/).
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* If the PR is a bug fix, it has to include a new unit test that fails before the patch is merged.
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* If the PR is a new feature, it has to come with a suite of unit tests, that tests the new functionality.
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* In any case, all the PRs have to pass the personal evaluation of at least one of the [maintainers](maintainers.md).
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* In any case, all the PRs have to pass the personal evaluation of at least one of the [maintainers](MAINTAINERS.md).
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### Format of the commit message
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docs/SUMMARY.md

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# Table of contents
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* [README](README.md)
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* [LICENSE](LICENSE.md)
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* [MAINTAINERS](MAINTAINERS.md)
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* [CODE\_OF\_CONDUCT](docs/CODE_OF_CONDUCT.md)
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* [CONTRIBUTING](docs/CONTRIBUTING.md)
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