A freely available open-source deep learning book that combines mathematical theory with runnable code. Readers can modify and execute Python/Jupyter examples directly while studying the underlying formulas.
Project overview
A freely available open-source deep learning book that combines mathematical theory with runnable code. Readers can modify and execute Python/Jupyter examples directly while studying the underlying formulas.
Project type
Model Development
Use cases
Learning & Education
Deployment
Refer to project documentation
License
Apache-2.0
Best for
Students and practitioners who want to understand both the math and engineering skills needed for applied deep learning.
Readers who benefit from modifying and running code to map mathematical formulas to practical implementations.
Key capabilities
A unified open-source resource teaching deep learning concepts, mathematics, and code with runnable examples.
Provides modifiable and runnable code to demonstrate practical problem-solving and map mathematical formulas directly to code.
Limitations and risks
The project primarily targets Chinese readers, with the English version driving new content updates.
Getting started
Install the source code as instructed in the book and run the provided Python and Jupyter notebook examples.