Deep Learning: Foundations and Concepts

Great overview of modern neural networks. It's really a little bit like if you take the chapter on neural networks in Bishop's previous book (Pattern Recognition and Machine Learning) and imagine that expanded out with all the new ideas in neural networks from the past 15 years. This is that book. I got a lot out of the chapters on Transformers/Attention, Diffusion and Graph Neural Networks. Also very readable.

Very well Scripted and Illustrated

Good insightful book

It is so satisfying to see in each chapter how the authors start with basic, simple concepts and then lead you to the amazing capabilities of deep learning.

I have many books on Deep Learning and this is the first that presents the subject in a coherent, well thought out manner. Each topic is introduced carefully, explained well with relevant pointers to other fields/work. The underlying statistics are clearly presented in a logical manner. The connections between many of the techniques used are clearly exposed. It's a delight to read and I would recommend it wholeheartedly.

Great textbook for anyone serious about mastering deep learning. Its exceptional balance of theoretical depth and practical application, combined with high-quality print and well-designed exercises, makes it a standout resource in the field.

Hundreds of formulae in the book inverted the closing bracket of the left-hand-side of the equation with the "=" sign. See the below example with Bayes' Theorem. Fortunately the Amazon returns policy was straightforward.

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