Description
Dive into Deep Learning is an interactive textbook designed to teach deep learning concepts and applications. It is available in both English and Chinese, making it accessible to a global audience. The book covers a wide range of topics, including linear neural networks, convolutional neural networks, recurrent neural networks, and modern architectures like Transformers.
Read More
The textbook is unique in its approach, combining theoretical explanations with practical examples using popular frameworks such as PyTorch, TensorFlow, and MXNet. Each section is accompanied by executable Jupyter notebooks, allowing learners to modify code and experiment with hyperparameters to gain hands-on experience.
Dive into Deep Learning is widely used in academia, with over 500 universities across 70 countries incorporating it into their curriculum. The book also provides resources like lecture slides, assignments, and instructional videos to support educators and students.
The second edition of the book introduces new content, including implementations using PaddlePaddle and updates to align with publishing standards and academic norms. The book is available in both online and print formats, with the print version offering additional features like improved styling and terminology annotations.
Dive into Deep Learning is supported by a vibrant community, where learners can engage in discussions and share insights. The book's open-source nature encourages contributions from the community, enhancing its content and keeping it up-to-date with the latest advancements in deep learning.
- CategoryAI Research Assistants
- Pricing ModelFree
- DeploymentCloud
- PlatformsWeb, Print
Dive into Deep Learning's Core Features
Interactive textbook with practical examples
Covers PyTorch, TensorFlow, MXNet, and PaddlePaddle
Executable Jupyter notebooks for hands-on learning
Used by over 500 universities globally
Available in English and Chinese
Includes lecture slides, assignments, and videos
Open-source with community contributions
Print and online versions available
How to use Dive into Deep Learning?
Access: Visit the Dive into Deep Learning website
Explore: Navigate through the chapters and topics
Practice: Use Jupyter notebooks for hands-on exercises
Engage: Join the community for discussions and updates
Dive into Deep Learning's Use Cases
- Academic Learning
- Self-Study
- Research Reference
- Practical Exercises
- Community Engagement
