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A comment on The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer. Parent comment
- Understanding deep learning by Prince[1]
- Deep learning - Foundations and concepts by Bishop[2]
- Deep learning architectures - mathematical approach - Calin[3]. Though each chapter seems to only have a handful of exercises.
- Mathematical theory of deep learning by Petersen et al[4]. Only handful of exercises each chapter as well.
I think Bishop is probably the best one, balancing between not too difficult but not too easy either.
[1] https://udlbook.github.io/udlbook/
[2] https://www.bishopbook.com/
[3] https://link.springer.com/book/10.1007/978-3-030-36721-3
[4] https://arxiv.org/abs/2407.18384
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- Understanding deep learning by Prince[1]
- Deep learning - Foundations and concepts by Bishop[2]
- Deep learning architectures - mathematical approach - Calin[3]. Though each chapter seems to only have a handful of exercises.
- Mathematical theory of deep learning by Petersen et al[4]. Only handful of exercises each chapter as well.
I think Bishop is probably the best one, balancing between not too difficult but not too easy either.
[1] https://udlbook.github.io/udlbook/
[2] https://www.bishopbook.com/
[3] https://link.springer.com/book/10.1007/978-3-030-36721-3
[4] https://arxiv.org/abs/2407.18384