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Added roadmap (#394)
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tovbinm authored Oct 19, 2019
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4 changes: 4 additions & 0 deletions CONTRIBUTING.md
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This page lists recommendations and requirements for how to best contribute to TransmogrifAI. We strive to obey these as best as possible. As always, thanks for contributing – we hope these guidelines make it easier and shed some light on our approach and processes.

# Getting started

Please join the community on Gitter [![Chat](https://badges.gitter.im/salesforce/TransmogrifAI.svg)](https://gitter.im/salesforce/TransmogrifAI?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge). Also please make sure to take a look at the project [roadmap](ROADMAP.md) to see where are headed.

# Issues, requests & ideas

Use GitHub [Issues](https://github.com/salesforce/TransmogrifAI/issues) page to submit issues, enhancement requests and discuss ideas.
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16 changes: 16 additions & 0 deletions ROADMAP.md
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# The TransmogrifAI Roadmap

## Short Term

- Implement Python interface for loading and evaluating TransmogrifAI models - [#393](https://github.com/salesforce/TransmogrifAI/issues/393)
- Extend Python interface to allow defining workflows & train models with existing TransmogrifAI readers, stages etc. - [#393](https://github.com/salesforce/TransmogrifAI/issues/393)
- Standatize versioning of TransmogrifAI models format and implement verification for safe execution - [#397](https://github.com/salesforce/TransmogrifAI/issues/397)
- Implement deep learning support, e.g. an ability to load an TensorFlow models and score them - [#288](https://github.com/salesforce/TransmogrifAI/issues/248), [#355](https://github.com/salesforce/TransmogrifAI/pull/355)
- Investigate integration with [JohnSnowNLP](https://github.com/JohnSnowLabs/spark-nlp) library, since it has some many fancy operations that we could use



## Long Term

- Extend Python interface to allow defining custom readers & stages with Python code snippets - [#393](https://github.com/salesforce/TransmogrifAI/issues/393)
- Allow exporting TransmogrifAI models in MLeap or other popular format, e.g. ONNX

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