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# Natural Language Processing
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# A Code-First Intro to Natural Language Processing
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This course is being taught in the [University of San Francisco's Masters of Science in Data Science](https://www.usfca.edu/arts-sciences/graduate-programs/analytics) program, summer 2019. The course is taught in Python with Jupyter Notebooks, using libraries such as sklearn, nltk, pytorch, and fastai.
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You can find out about the course in [this blog post](https://www.fast.ai/2019/07/08/fastai-nlp/) and all [lecture videos are available here](https://www.youtube.com/playlist?list=PLtmWHNX-gukKocXQOkQjuVxglSDYWsSh9).
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This course was originally taught in the [University of San Francisco's Masters of Science in Data Science](https://www.usfca.edu/arts-sciences/graduate-programs/analytics) program, summer 2019. The course is taught in Python with Jupyter Notebooks, using libraries such as sklearn, nltk, pytorch, and fastai.
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## Table of Contents
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The following topics will be covered:
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All that to say, don't worry if you don't understand everything at first! You're not supposed to. We will start using some "black boxes" and then we'll dig into the lower level details later.
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To start, focus on what things DO, not what they ARE.
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To start, focus on what things DO, not what they ARE.

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