It is an open-source, interactive Chinese-language deep learning textbook suitable for computer science students, AI-transitioning engineers, researchers, and others who want to systematically learn deep learning theory and practice.
A basic knowledge of Python programming is recommended. The book starts from mathematical basics, and beginners can study in order, acquiring the necessary mathematics and framework knowledge through practice.
The second edition mainly provides implementation code for several mainstream frameworks, including PyTorch, TensorFlow, NumPy/MXNet, PaddlePaddle, and JAX, to facilitate user choice.
Yes. The second edition, Hands-on Deep Learning (PyTorch Edition), is available in print on JD.com and Dangdang; the content is broadly similar to the online version, convenient for offline reading.
All content is open-source on GitHub; it is recommended to follow its GitHub repository to obtain the latest code and chapter updates.
The PyTorch version of the instructional videos can be viewed on Bilibili, and the course livestream recordings are also provided there, synchronized with the textbook content.
An AI education platform founded by Andrew Ng, offering systematic AI courses from beginner to advanced levels along with industry insights to help learners build professional skills and enhance their career competitiveness.
An educational platform focused on machine learning that helps developers master machine learning skills from fundamentals to cutting-edge applications through systematic tutorials, hands-on code practice, and free courses.
