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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth to provide a starting point on the path to actually becoming an applied machine learning scientist.
Features
- Freely available for everyone
- Sufficient technical depth to provide a starting point on the path to actually becoming an applied machine learning scientist
- Runnable code, showing readers how to solve problems in practice
- Rapid updates, both by us and also by the community at large
- Complemented by a forum for interactive discussion of technical details and to answer questions
- Interactive examples with self-contained code
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