d2l-ai/d2l-en

Dive into Deep Learning: an interactive deep learning book on Jupyter notebooks, using the NumPy interface.


repo name	d2l-ai/d2l-en
repo link	https://github.com/d2l-ai/d2l-en
homepage	https://d2l.ai
language	Python
size (curr.)	183895 kB
stars (curr.)	3998
created	2018-10-09
license	Other

Dive into Deep Learning (D2L Book)

Book website | STAT 157 Course at UC Berkeley, Spring 2019

This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code.

Our goal is to offer a resource that could

be freely available for everyone;
offer sufficient technical depth to provide a starting point on the path to actually becoming an applied machine learning scientist;
include runnable code, showing readers how to solve problems in practice;
allow for rapid updates, both by us and also by the community at large;
be complemented by a forum for interactive discussion of technical details and to answer questions.

If you find this book useful, please star (★) this repository or cite this book using the following bibtex entry:

@book{zhang2020dive,
    title={Dive into Deep Learning},
    author={Aston Zhang and Zachary C. Lipton and Mu Li and Alexander J. Smola},
    note={\url{https://d2l.ai}},
    year={2020}
}

Endorsements

Contribute (learn how)

This open source book has benefited from pedagogical suggestions, typo corrections, and other improvements from community contributors. Your help is valuable for making the book better for everyone. We will acknowledge each D2L contributor in the book and send a free book (hard copy) to the first 100 contributors when it is published.

Dear D2L contributors, please email your GitHub ID, name, and mailing address to d2lbook.en@gmail.com. Thanks.

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