hamelsmu/Seq2Seq_Tutorial
Code For Medium Article "How To Create Data Products That Are Magical Using Sequence-to-Sequence Models"
This project helps data scientists and machine learning engineers learn to build sequence-to-sequence models. You'll use real-world GitHub issue data to understand how to turn text inputs into new, generated text outputs. It's designed for data professionals looking to expand their skills in natural language generation.
139 stars. No commits in the last 6 months.
Use this if you are a data scientist or machine learning engineer who wants to learn how to build and implement sequence-to-sequence models for natural language generation.
Not ideal if you are a business user looking for a ready-to-use application; this is a tutorial for building the underlying technology.
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139
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50
Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Dec 07, 2022
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