Dive into Deep Learning now supports PyTorch. The first 8 chapters are ready with more on their way. Thanks to DSG IIT Roorkee DSG_IITR, particularly Anirudh Dagar who adapted the code into PyTorch. More at D2L.ai. Mu Li Alex Smola Zachary Lipton Aston Zhang

Dive into Deep Learning now supports TensorFlow. The first 7 chapters are released today with more on their way. Special thanks to Yuan (Terry) Tang and Abhinav Prakash for contributing code and our Google friends Jeff Dean 👩‍💻 Paige Bailey and Tomer Kaftan. More at D2L.ai.

Dive into Deep Learning v0.15.0 is released! More chapters are in PyTorch and TensorFlow. More chapters are close to v1.0. Adopted at 140 universities: if you use D2L to teach, apply for free computing resources by Nov 22. Check out D2L.ai

Check out our brand-new attention chapter, such as simpler illustrations using Nadaraya-Watson kernel regression (1964) before Bahdanau attention. Now PyTorch adaptation is complete for Vol.1. The first 1/3 part is also translated into Chinese and Turkish. D2L.ai

The d2l.ai chapter on Attention just got a lot more attention. d2l.ai/chapter_attent… now including Bahdanau attention, Watson Nadaraya, Self-attention and much more background. Just in time for school! Thanks Aston Zhang and everyone on the Dive into Deep learning (D2L.ai) team.

The Chinese translation of D2L (Chap 1--8) is available, with implementations in Apache MXNet, PyTorch and TensorFlow! 《动手学深度学习》第二版预览版：zh-v2.d2l.ai GitHub地址：github.com/d2l-ai/d2l-zh

It's not the lack of resources that holds back people from getting started with deep learning. It's a combination of procrastination and lack of guidance. This is why my top recommendation is "Dive into Deep Learning". It gets you going right away! d2l.ai

Looks like the excellent #DeepLearning book by Aston Zhang Zachary Lipton Mu Li Alex Smola has been published to arXiv! arxiv.org/abs/2106.11342 While the book is thought for online reading at d2l.ai, I still think that having a printable version is Big News!

Introducing a new option to run the D2L book for free: using SageMaker Studio Lab d2l.ai

The #Portuguese translation for #D2L is up at pt.d2l.ai. Muito obrigado a Dalcimar Casanova Ph.D., Lucas Hendges e Fabio Kurpel por seu excelente trabajo! Join us on github.com/d2l-ai/d2l-pt.

While ConvNeXt (2022) further sparks the debate between CNNs and transformers for vision, D2L.ai added a CNN design section covering ResNeXt-itication Saining Xie et al, RegNets Radosavovic et al, ConvNeXt Zhuang Liu et al. Preview at: preview.d2l.ai/d2l-en/master/…

The deep learning field has been growing fast. Our D2L book just added topics on scalability of transformers and very recent large-scale pretraining methods: d2l.ai/chapter_attent… More updates are on the way 😃

Announcing the Preview Edition of Dive into Deep Learning Dive into Deep learning (D2L.ai) containing our nightly builds. Check them out at preview.d2l.ai/d2l-en/master/. Thanks Mu Li Aston Zhang Zachary Lipton Anirudh Dagar @goldpiggy95 and many volunteers for all the work!

Chinese version 2.0🎉 zh.d2l.ai 🙏37k stars, 248 contributors, multi-frameworks by & for our growing community: 🆙Upgraded physical book featuring PyTorch implementation Amazon Science 🆕New @PaddlePaddle_ implementation by Baidu Inc., reviewer Shuai Zhang

Welcome aboard!

Our deep learning book goes 1.0 beta🎉 📕Forthcoming on Cambridge Univ Press (w PyTorch) 🆕JAX implementation 🆕Reinforcement Learning 🆕Gaussian Processes 🆕Hyperparameter Optimization - Thank 500 contributors & 400 univs for choosing! - Free at D2L.ai (1/5)

Thrilled that our 'Dive into Deep Learning' book, now published by Cambridge University Press, is the Top New Release on Amazon! To ensure accessibility and affordability, we, the authors, have waived our royalties. Plus, it's always available for free at D2L.ai