NEURAL NETWORKS: A CLASSROOM APPROACH, 2ND EDN

To be very clear, I am not a fan of this book. As an ECE Student, I bought this book as it was the prescribed textbook from my University.-- The book is good enough for the syllabus but I do not like the way it has been written. Even for a person who has some experience in Deep learning, the way the information has been was not very reader-friendly.-- There are a lot of mathematical equations given, which is a good thing since Deep Learning is all about maths, however, I felt that the book tend to overcomplicate simple things and directly go too mathematical right from the start!-- It is definitely not recommended for any noob who has no prior experience in any kind of learning algorithm or has a strong math background.-- I felt that the content was "okay", but the author definitely needs to work on the clarity of the concept and explanation of keywords in a sidenote or something.-- Having read the most popular book for Deep Learning by Ian Goodfellow -  Deep Learning , This book seems rather primitive -- since Ian Goodfellow did explain the concepts much better than Satish Kumar even though it is much more advanced compared to this book.-- Last but not the least, I did feel that the content was quite outdated with rather older unnecessary concepts, compared to the current industry standards.Verdict: Not really recommended. There are better options available.

This book is superb.I have read Bishop's book also on neural networks, but this book by far provides the best possible exposition to the field. The author has provided good motivation for considering multi layered neural nets and has gone into more advanced materials like recurrent/attractor neural nets etc. The best part is that the author does not sacrifice mathematical rigour to make the material easier. The writing is so lucid that the reader does not stumble at the notations or exposition anywhere. Also, the initial exposition at the beginning of every chapter makes sure that the reader doesn't get numbed by jargon and math in the beginning, rather gets curious about what all the chapter has to offer. In all, this book is a masterpiece in statistics/ machine learning. If you are serious about understanding all the nuances, both theoretical and applied start reading this book.

The quality of paper used in this book is nice. Except that there is nothing is this book that a beginning like me can appreciate. The author has given extra theory to the concepts that it makes it even more confusing. And the style of writing is also very complicated, I don't know why? It could have been a lot simple. I bought this because my university told me to. If you have previously worked in the field, probably you might find it useful. But, it's waste of money for beginners like me 👎🏻👎🏻👎🏻

Well how do you say about it...Let's say there are 3 types of books1.A prof/scientist talks with himself while writing the book (those books are awful to read)2.He/she writes as he/she is giving an elaborated seminar to fellow other researchers (nearly 80% science book market belong to this category)3.He/she writes as if he is interacting with a student(this book are rare and enjoyable)[e.g-H.c. verma,Griffiths's electrodynamics)Well this book belongs in the 2nd category and without certain prerequisites you can't learn it. It is not for beginners but if you have a good knowledge of mathematics and statistics you can milk almost everything from this book.

This book is really a good one for a begginer to understand the inside of NN.

Nyc

It's good if you are studying neural networks for the first time. It has really good examples and covers almost everything in the field of neural networks, and provides lots of references.

I think more analogies could have been given.

Il libro spiega chiaramente le varie architetture delle reti neurali dalle SOM alle MLP. Inoltre tratta delle support vector machine.Inoltre argomenta chiaramente come queste strutture debbano essere usate per il pattern recognition.Per finire, ma è il motivo per cui ho comprato il libro, ogni struttura è accompagnata dal proprio programma scritto in MATLAB!!!