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README.md

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# Seq2Seq_Tutorial
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Code For Medium Article "How To Create Data Products That Are Magical And Useful Using Sequence-to-Sequence Models"
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[![GitHub license](https://img.shields.io/github/license/hamelsmu/Seq2Seq_Tutorial.svg)](https://github.com/hamelsmu/Seq2Seq_Tutorial/blob/master/LICENSE)
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## Sequence-to-Sequence Tutorial with Github Issues Data
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Code For Medium Article: ["How To Create Data Products That Are Magical And Useful Using Sequence-to-Sequence Models"]()
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## Resources:
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1. [Tutorial Notebook](./notebooks/Tutorial.ipynb): The Jupyter notebook that coincides with the Medium post.
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2. [seq2seq_utils.py](./notebooks/seq2seq_utils.py): convenience functions that are used in the tutorial notebook to make predictions.
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3. [ktext](https://github.com/hamelsmu/ktext): this library is used in the tutorial to clean data. This library can be installed with `pip`.
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4. [Nvidia Docker Container](https://hub.docker.com/r/hamelsmu/seq2seq_tutorial/): contains all libraries that are required to run the tutorial. This container is built with Nvidia-Docker v1.0. You can run this container by executing `nvidia-docker run hamelsmu/seq2seq_tutorial/` after installing **Nvidia-Docker v1.0.** Note: I have not tested this on Nvidia-Docker v2.0.
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