https://github.com/deeplearning4j/dl4j-examples
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CONTRIBUTORS.md
# Contributing to dl4j-examples

Thanks for your interest in Deeplearning4j's examples. Our goal is to bring fast, open-source deep learning to all JVM-based communities.

## Getting Started

Here are Deeplearning4j's [open issues are here](https://github.com/deeplearning4j/deeplearning4j/issues). In time, we'll tag issues that would make a good first pull request for new contributors. An easy way to get started helping the project is to *file an issue*. You can do that on the Deeplearning4j issues page by clicking on the green button at the right. Issues can include bugs to fix, features to add, or documentation that looks outdated. 

For some tips on contributing to open source, this [post is helpful](http://blog.smartbear.com/programming/14-ways-to-contribute-to-open-source-without-being-a-programming-genius-or-a-rock-star/).

## Contributions

Deeplearning4j welcomes contributions from everyone.

Contributions to Deeplearning4j should be made in the form of GitHub pull requests. Each pull request will
be reviewed by a core contributor (someone with permission to land patches) and either landed in the
main tree or given feedback for changes that would be required.

## Pull Request Checklist

- Branch from the master branch and, if needed, rebase to the current master
  branch before submitting your pull request. If it doesn't merge cleanly with
  master you may be asked to rebase your changes.

- Commits should be as small as possible, while ensuring that each commit is
  correct independently (i.e., each commit should compile and pass tests). 

- Don't put submodule updates in your pull request unless they are to landed
  commits.

- If your patch is not getting reviewed or you need a specific person to review
  it, you can @-reply a reviewer asking for a review in the pull request or a
  comment.

- Add tests relevant to the fixed bug or new feature.  

## Conduct & License

We follow the [Rust Code of Conduct](http://www.rust-lang.org/conduct.html).

All code in this repository is released under the Apache Software Foundation License, 2.0, and by contributing to this repository, you agree to release your contribution under that same license. 
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