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Can any practitioners / experts out there comment on the range of topics? For example, I understand the book to be introductory, and so the scope is likely som
by kkylin 11y ago
Can any practitioners / experts out there comment on the range of topics? For example, I understand the book to be introductory, and so the scope is likely somewhat limited. But how close does it get you to the ANNs currently in use, at least conceptually if not in complete detail? Thanks!
- ericjang 11y agoNon-expert DL practitioner here. The coverage is very good - if I were running some kind of "Deep Learning onboarding class" for a university or tech company, this is what I would present. My favorite aspect of this book is that it provides a graphical models interpretation of DL methods, which is the most powerful perspective we have right now to reason about model design (instead of some large black box function that we train end-to-end without knowing what's in between). It also explains some fairly recent models and techniques well (VAE, DCGAN, regularization) that form the basis of more complex architectures. If you understand the models here, you should be able to understand the design choices made in more complex architectures. Thanks to Goodfellow, Bengio, and Courville for this excellent work.
- kkylin 11y agoGreat, that's very helpful to know. Thanks!