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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

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Dive into Deep Learning (D2L Book)

Build Status

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

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 [email protected]. Thanks.

Chinese version | Discuss and report issues

Cite

Please use the following bibtex entry to cite this book:

@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}
}

Other Information

License Summary

This open source book is made available under the Creative Commons Attribution-ShareAlike 4.0 International License. See the LICENSE file.

The sample and reference code within this open source book is made available under a modified MIT license. See the LICENSE-SAMPLECODE file.

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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

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  • Python 61.8%
  • TeX 23.7%
  • HTML 12.9%
  • Shell 1.6%