Dive into Deep Learning (D2L Book)

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

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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 contributor in the book and send a free book (hard copy) to each contributor when it is published.

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

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Name		Name	Last commit message	Last commit date
Latest commit History 20 Commits
build		build
chapter_appendix		chapter_appendix
chapter_computational-performance		chapter_computational-performance
chapter_computer-vision		chapter_computer-vision
chapter_convolutional-neural-networks		chapter_convolutional-neural-networks
chapter_crashcourse		chapter_crashcourse
chapter_deep-learning-basics		chapter_deep-learning-basics
chapter_deep-learning-computation		chapter_deep-learning-computation
chapter_how-to-use		chapter_how-to-use
chapter_introduction		chapter_introduction
chapter_linear-networks		chapter_linear-networks
chapter_multilayer-perceptrons		chapter_multilayer-perceptrons
chapter_natural-language-processing		chapter_natural-language-processing
chapter_optimization		chapter_optimization
chapter_preface		chapter_preface
chapter_recurrent-neural-networks		chapter_recurrent-neural-networks
contrib		contrib
d2l		d2l
graffle		graffle
img		img
.gitignore		.gitignore
.gitmodules		.gitmodules
Jenkinsfile		Jenkinsfile
Makefile		Makefile
README.md		README.md
STYLE_GUIDE.md		STYLE_GUIDE.md
environment.yml		environment.yml
setup.py		setup.py

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Dive into Deep Learning (D2L Book)

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