Understanding 99% of Artificial Neural Networks : Introduction & Tricks

Rating:
Summary: Recommended for beginners
Review: It was warmly welcomed to read an Introduction to Neural Networks without an intimidating level of mathematics in the presentation. Recommended for beginners.

Rating:
Summary: The Title of the Book is an Unfulfilled Goal.
Review: Most striking about the book is the poor grammar. True, we engineers are not known to be a linguistically elegant lot, but the grammatical errors in this text do get in the way of a clear explanation of the topic. It should have been proofread by a native English speaker. Regarding the technology explained, the book misses the mark because it doesn't simplify the areas in which people truly have difficulty. Specifically, it doesn't clearly describe how error is "backpropagated" in the standard backpropagation neural net. That topic is the core of the subject and the book misses it. The author merely baby talks the easy parts of the subject and gives misleading pseudocode. There are many books that are much better at presenting simple, intuitive explanations of the theory. Lastly, the book assumes that backprop and Kohonen nets are "99% of artificial neural networks". That is an outdated view. Today, there are *many* types of networks (e.g., recurrent backpropagation nets, reinforcement learning nets, competitive learning nets, counterpropagation nets, neural gas nets, growing neural gas nets, etc.) None of these is addressed at all. Frankly, I would have been minimally satisfied with a clear explanation of the backprop and the Kohonen algorithms, but even that was lacking. I give it the second star only because the goal was a worthy one.

Rating:
Summary: A good book to read, and a clear guide to understand nets
Review: Neural Networks seems to be too complicated for average people.
However, this book makes a clear description of the subject.
If you want to read a work about neural nets and UNDERSTAND what is says, this is your book.
As a matter of fact, it contains two items that are not so easy to find in other texts: a) A guide to help you if you want to build your own network b) The source code of the examples.
A very nice book to read, for students, and the ones that would like to know something about this subject

Rating:
Summary: An introduction to the field for undergraduate students
Review: The book gives an introduction to the field, and is primarily aimed at undergraduate students from computer science or mathematics. I think that this text could also interest ordinary people.

Rating:
Summary: A book for students with no previous experience.
Review: The first chapters present the basic concepts of artificial neural networks, but the work makes focus in backprop nets and its variants, so the computational capabilities of the basic network architectures involved are explained at the end of the book. This makes the subject more accessible to students and practitioners with no previous experience.

Rating:
Summary: A book for students with no previous experience.
Review: The first chapters present the basic concepts of artificial neural networks, but the work makes focus in backprop nets and its variants, so the computational capabilities of the basic network architectures involved are explained at the end of the book. This makes the subject more accessible to students and practitioners with no previous experience.

Rating:
Summary: An editor's nightmare; a reader's disappointment
Review: There are two hurdles to overcome with this "book." The first is the challenging English. I can safely say that I could decipher only about 85% of the English, from a linguistic standpoint. Critical statements about important issues regarding neural nets are so scrambled in word order and choice of vocabulary that they are simply not understandable to this multi-lingual reviewer. While this could have been remedied by employing a competent bi-lingual translator to edit the work, the author obviously chose not to engage one. The second hurdle rests in the concepts of neural nets. These are not explained in a useful way.

My hope was that the Visual Basic code might be useful. The author's choice of VB Script (ASP 3), rather than a more strongly typed language leaves the reader in a position of having to guess the data types that are being used (seldom declared at all). Even VB 6 would have been a better choice and made the code easier to understand. Variable names are either cryptic or (I'm guessing here) Portuguese . A conscientious use of descriptive variable names would have produced self-documenting code. My criticism here is that the code itself is obtuse.

The text is actually only 56 pages long, and that littered with large, nearly meaningless diagrams that clarify little, and sophomoric philosophical comments and sweeping generalities. In such a brief work, the loss of focus is exasperating.

The table of contents contains 82 entries for a book of 120 pages (including back matter). The index is useless. For example, there are separate entries for "artificial", "Artificial" and "ARTIFICIAL", each listing identical page references for more than 1/3 of all the pages in the book. In the bibliography, all but one of the entries is prior to 1993, and many are incomplete references, such as an author, year and title, but no publisher or named periodical.

Why should you care about all these shortcomings? I am already familiar with neural net theory, and yet I could not understand much of the text. I am an experienced software developer, and yet I have difficulty following the sample code in the appendix.

SUMMARY: The entirety of this material should have been cleaned up linguistically, then submitted to a magazine as an article. It hardly comprises sufficient content for a book. As it stands, it fails to fulfill the promise of its title. A reader new to neural nets is unlikely to be satisfied with their expenditure of time and money here. Sorry.

P.S. As you look through the other reviews of this book, it's not too difficult to identify the numerous "planted" ones. They subvert the usefulness of the Average Rating. You would be wise to read all the reviews.


Rating:
Summary: An introduction to the field of neural networks
Review: This book is an outstanding introduction to this field of computer science.

The book includes an appendix with computer source code, but it was designed for ordinary people, who don't know anything about neural networks and want to introduce in this subject.