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Dive into Deep Learning: an interactive deep learning book with code, math, and discussions

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Dive into Deep Learning (D2L Book)

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

This version is based on the classic ndarray interface.

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.

Chinese version | Discuss and report issues

Cite

Please use the following bibtex entry to cite this book:

@book{zhang2019dive,
    title={Dive into Deep Learning},
    author={Aston Zhang and Zachary C. Lipton and Mu Li and Alexander J. Smola},
    note={\url{http://www.d2l.ai}},
    year={2019}
}

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Dive into Deep Learning: an interactive deep learning book with code, math, and discussions

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  • Python 70.9%
  • TeX 21.0%
  • HTML 7.5%
  • Shell 0.6%