Preface

http://d2l.ai/chapter_preface/index.html

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The first thread for d2l-en with pytorch implementations.

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Thank you and your team :cn:

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Thanks a lot for writing this nice book.
I like read pdf e-books, How can I download the pdf e-book in pytorch version

Hello,forum! :star_struck: :slightly_smiling_face:

Thank you and the work on deep learning your team have done!

I’ve failed many times but this time I am going to learn deep learning coz now I implement top down approach and this book seems like a nice place to start…

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I’m collecting the knowledge with Obsidian. I hope this helps me to keep up with the project and push myself to do it. Hello forum!

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The road to Deep Learning ! Hello Forum! :sparkling_heart:

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Hello, forum :smiling_face_with_three_hearts: :smiling_face_with_three_hearts: :smiling_face_with_three_hearts:
Planning on a deep dive into Deep Learning.

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Congrats on the formal release of V1.0.0!

Thanks for this wonderful knowledge!

Thank you so much! I have read Goodfellow (2016), which is excellent, but have needed just the right vehicle to marry its concepts to the practical matters of practitioners, especially insofar as the leading frameworks (PyTorch, TensorFlow, etc.) are concerned. This book is perfect for that!

Coming here! Start learning now~

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Never say never, better late than never,

Excited to learn from such awesome book. Let’s Get Started…

I get excited!. Looking to be excellent in the field and make a step toward AGI/AMI

Thanks for the great work

The only thing I don’t like about this book is that, a lot of implementation depends on a course specific abstraction, which makes the code slightly cleaner, but less compatible to native pytorch interface, and harder to adopt in my own future work. Is there an option for not having those in current version?