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<!--
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### THIS FILE WAS AUTOGENERATED! DO NOT EDIT! ###
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# file to edit: index.ipynb
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# command to build the docs after a change: nbdev_build_docs
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# Notebooks — Grokking Deep Learning by Andrew W. Trask
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# Grokking Deep Learning by Andrew W. Trask
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> https://www.manning.com/books/grokking-deep-learning
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<div style="text-align:center"><img style="width:100%" src="static/imgs/Cover.png"></div>
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- Grokking Deep Learning was written to help **give you a foundation in deep learning** so that you can **master a major deep learning framework**.
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- Requires no math background beyond basic arithmetic.
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- Doesn't rely on a high-level library that might hide what's going on.
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- Anyone can read this book and understand how deep learning really works.
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- You won't just read the theory, you'll discover it yourself.
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> (You can Buy the Book from [Manning Publications](https: //www.manning.com/books/grokking-deep-learning) or [Amazon](https://www.amazon.com/Grokking-Deep-Learning-Andrew-Trask/dp/1617293709)).
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This repo is home to notes & the code that accompanies Andrew W. Trask's "Grokking Deep Learning" book. It provides a solid foundation in deep learning so that you can master any major deep learning framework.
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The book requires no math background beyond basic arithmetic. It doesn't rely on a high-level library that might hide what's going on. Anyone can read the book and understand how deep learning really works. You won't just read the theory, you'll discover it yourself.
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> (You can Buy the Book from [Manning Publications](https: //www.manning.com/books/grokking-deep-learning) or [Amazon](https://www.amazon.com/Grokking-Deep-Learning-Andrew-Trask/dp/1617293709)).
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# Roadmap
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"Grokking Deep Learning" has 16 Chapters:
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"Grokking Deep Learning" has 16 chapters. We provide links for the available notebooks:
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1. Introducing Deep Learning: Why you should Learn It?
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2. fundamental Concepts: How Do Machines Learn?

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