动手学深度学习Translation site

In today’s AI wave, mastering deep learning has become an essential skill in the tech field. For Gen Z and internet users, finding a practical and easy-to-use textbook is crucial. Today, we recommend ‘Dive into Deep Learning,’ an open-source textbook that will help you easily step into the world of deep learning.

Website Introduction

‘Dive into Deep Learning’ is an open-source deep learning textbook for Chinese readers, offering implementations in PyTorch, NumPy/MXNet, TensorFlow, and PaddlePaddle. It has been adopted by over 500 universities in more than 70 countries worldwide.

Key Features

• Multi-framework support: Covers implementations in PyTorch, NumPy/MXNet, TensorFlow, and PaddlePaddle, providing diversity.
• Executable Jupyter Notebooks: Each section is an executable Jupyter notebook, allowing readers to freely modify code and hyperparameters for immediate feedback.
• Formulas + Illustrations + Code: Combines text, formulas, and illustrations to explain deep learning models and algorithms, providing code demonstrations with real data for an interactive learning experience.

Related Projects

The English version of this book has been adopted by over 500 universities in more than 70 countries, reflecting its wide influence and recognition.

Advantages

‘Dive into Deep Learning’ is praised as ‘the most suitable textbook for industrial R&D engineers,’ and its hands-on learning approach is deeply loved by readers.

Pricing

This book is an open-source project; the electronic version is available for free access and download. The printed version can be purchased on platforms like JD.com and Dangdang.

Summary

‘Dive into Deep Learning’ is co-authored by Amazon scientists and Carnegie Mellon University professors, dedicated to providing practical and discussable deep learning resources. Through these innovative features, users can gain practical experience and theoretical knowledge in deep learning, aiding growth in the AI field.