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Share your thoughts with other customers. Write a customer review. Read reviews that mention neural networks neural network well written worked examples linear algebra network design deep learning end of each chapter artificial neural complex mathematical studying neural book makes excellent book good book networks textbook matlab math authors background field.
There was a problem filtering reviews right now. Please try again later. This is a fantastic book which introduces various mathematical concepts vectors, matrices, derivatives, optimization methods , and shows the mathematical derivations of the learning algorithms for several kinds of neural network types including multi-layer perceptrons and recurrent neural networks.
There are several general features of this book which make it a truly superb for going all the way from absolute novice to true expert: If a person with some past exposure to vectors and derivatives wanted to learn about neural networks, from zero to expert, then this would be the very first book I would recommend!
In fact, I think a person would do very well if this were their only book until reaching advanced understanding at which point I would recommend "graduating" to the excellent "Deep Learning" book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. A minor bittersweet aspect of experiencing this fantastic book is that many other textbooks will seem particularly lame by comparison.
Note that this book covers multi-layer perceptrons and recurrent-neural networks in great detail, but does not cover convolutional neural networks used by most image recognition systems today.
However, I think this book represents the best path to being ready to learn about more specialized neural network designs, and I think the extra study required to understand a network like a convolutional neural network would be relatively easy. Seems like an excellent book so far I tried about 10 other books on Neural networks, and always got stuck after the first chapter.
It explains the mathematics very nicely before it is used with Neural networks, and there are loads, and loads of worked examples. As long as you go through the worked examples, you can learn the material. The book refers a lot to Matlab, I dont think you need Matlab to understand the book, but will get more out of the book if you have Matlab. I used Mathematica for symbolics, when studying the book, I suppose I could have used Matlab instead, but you will need some symbolic software A very excellent and readable book.
They also give it away for free on the internet, but I recommend getting the book, as saves hassle of printing stuff out, and you need a hard copy, to write notes on. A curious thing, an excellent textbook in my opinion the best on the subject , and apparently they have a set of instructional videos to go with it. Why don't they just post the instructional videos on youtube, then charge bucks for the book. I would still consider the excellent value at that price. I think the goal of the book, is to prop up Matlab's position as number 1 piece of software for Neural networks.
But seriously, a book that helps you learn and study neural networks, and the ONLY book that I have come across so far, that seems to do a good job of explaining. A lot of books seems to have an easy first chapter to sell the book, then go off the cliff, but this seems linear throughout So, lots of good points, would recommend, especially if you find, like me you got bogged down in other texts. This textbook is hands down the most well written Neural Networks textbook available.
The notation and illustrations used make this text highly accessible to absolutely anyone interested in the subject - irregardless of your educational background. The content is as self contained as possible, and requires no more than the knowledge of rudimentary calculus as a pre-requisite. The book even includes well written chapters that exhaustively, yet simplistically, cover all the topics from linear algebra and basic mathematical optimization needed to understand the subject of neural networks at its most fundamental level.
There is a reason this book gets 4. Here is the primary author's webpage related to the textbook: This book offers an excellent introduction to the mathematics of neural networks.
The authors clearly have designed, built, and tested neural nets for many years. The book is pointed at learners early on in their study of neural nets, as it gives more information about the inner workings of each piece of the NN, and some tested advice about how and when to apply certain techniques. If you'd like to know the details about why NNs work, and how to design your own tools to build NNs, this is the book for you.
Complex material presented in clear and concise English. Covers widely used neural network designs and training algorithms. Worked problems are excellent, but "Exercises" need published answers, too. Book has no index, so looking up specific topics is all but impossible. Discontinuous pagination makes finding a specific item and easily returning to it quite difficult.
The review needs to point out that without a copy of MatLab the book's examples are all but intractable. The graphs in the book are utterly illegible. Very well written en the authors have taken pains to adhere to best pedagogical practices.
Money well spent if you: This is an amazing book that explains neural networks with worked examples and plenty of additional exercises. There is no other book on neural networks that is as comprehensive and clear. One person found this helpful 2 people found this helpful. See all 38 reviews. Most recent customer reviews. Published 5 months ago. Published 10 months ago. Published 11 months ago.
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