Deep Learning: Foundations and Concepts

Whhoowww hooo!! I was eagerly waiting to read this book. Thank you amazon.

Deep Learning: Foundations and Concepts is the best book to learn fundamentals of Neural Networks and Deep Learning. I have tried reading several other new books, but this is the best of them all, especially if you want to learn about Transformers.The Transformers chapter in this books goes step by step, builds concepts one by one, and completely demystifies how the Large Language Model technology works. If you want to really learn how LLMs work, and understand each important bit of the entire structure well, go for Christopher Bishop's book. The math of the Transformers chapter is not heavy, which makes the introduction easier to understand for many.One of the biggest advantages of this book is that the author tries to build an intuition for the reader, which is very helpful if you want to be a researcher and go deep into the subject and explore new areas on your own. Highly recommended book.INDIAN CUSTOMERS BEWARE of pirated copies: Amazon India sellers are selling pirated copies of this book. Do not buy pirated copies from Amazon India sellers. Buy directly from Springer Online store. Pirated copies have low quality binding, and it will come out very soon. Very disappointed to find that Amazon India seller ("shree Sai Fashion") sold me a pirated copy of the book.

It covers required mathematical details for deep learning.

The printing and binding of the book is very poor. I have the hardcover version. The pages are over trimmed so the content is at the edge of the pages.The diagrams and pictures are black and white, NOT in colour.

Great book if you have the patience to read each page by page. Readers should not even skip a single paragraph. Once that is followed, the result would be mind-blowing. You will end up having meaty concepts in Applied ML & Stats.And this book is not at all for casual reading. A serious approach with a pen & notebook will help, otherwise the content will appear very dull.

Though I loved the content of this book, it has a very poor binding. I am looking for some book binders in my locality to get all the pages fixed. Page quality is good and as expected though.

I ordered and replaced this book twice but it was disappointing to receive a book from which pages are coming out!!

Poor binding. Pages coming out.

This book continues the Bishops' tradition of writing accessible and clear yet rigorous treatment of machine learning/deep learning content.The transformers and diffusion chapters fantastic, and exactly what I was looking for.The authors share solutions to end of chapter questions which is perfect for students and self- learners alike.You can scan the book on their site, but this one is a *must have* for your bookshelf.If you need any more reason to purchase this book immediately, LeCun, Bengio and Hinton all wrote highly supportive reviews (see site).

El contenido es bueno, pero el libro llego golpeado en las esquinas, tengan mas cuidado al empacar para envio. Malo que tampoco no hay opcion de remplazo.

I'm feeling lucky.This is incredibly, unspeakably, impossibly good book.I've seen the book at the CVPR conference, and hesitated a bit before buying it. $90 after all.But I can't be happier with my purchase. It's simply the best book on Deep Learning - and on Machine Learning - I've seen in 20 years. It gives a very accessible and intuitive introduction in many topics - and, at the same time, preserves the mathematical rigor. For example, the chapter on transformers is the very, very best description of a topic I've seen so far.The book also contains all the info on the ML basics - from multivariate distributions to EM algorithm. Again, it is written very candidly - and, at the same time, preserves theoretical foundations. It is probably slightly less "mathy" than the "Pattern Recognition and Machine Learning" book by Bishop - which is a previous iteration of this text. But much, much more accessible as well. It explains "narrow" topics in plain English. You may read it in this textbook, and then go back to "Pattern Recognition" if you want to get a slightly deeper math for the same topic.Also the book is very recent and covers the hottest and most recent topics, like Diffusion Models.Saved me lots, lots of time and effort - instead of digging through a heap of research papers I can nos just read a chapter from this book.Many thanks to Chris Bishop for writing it!

Muito bom!

Bishop has done it again. His Pattern Recognition book was in the past the best ML book where we could learn all the fundamentals about machine learning models. Now, with this book, it basically does the same but with deep learning.I am reading it right now and, despite being a PhD in machine learning, I still learn with him. It is the best time investment that I am doing to learn machine learning.I absolutely recommend the book both for new PhD students or for senior researchers. Do not miss it.