Introduction to Neural Networks for C#, 2nd Edition

Introduction to Neural Networks for C#, 2nd Edition by Jeff Heaton

Introduction to Neural Networks for C#, 2nd Edition

Binding:
Perfect Paperback
Number of Pages:
428
ISBN:
1604390093
Product Group:
book
Publisher:
Heaton Research
Publication Date:
Oct. 2, 2008
BooksForGeeks.com ID:
1104

Reviews for Introduction to Neural Networks for C#, 2nd Edition

  1. A reasonable introduction to the concepts, but clearly a hasty port from Java

    Rated 3 out of 5 stars, September 12th, 2009

    First off - the positives.

    Coming into this book I had little knowledge of neural networks. I knew a little about how they were supposed to work, but with no real background trying to write one from scratch was an intimidating task. After leaving this book, I understand the concepts a lot better, and would be able to understand well written code in other peoples neural networks. But I think the broad reality is that writing one from scratch is always going to be challenging. But I understand the concepts, and neural network types and training methods, etc to know what kind of network I'd need to use in a given scenario, and how to train (or not) it.

    The negatives? Well its clearly a very hastily written port of the Authors own "Introduction to Neural Networks for Java". The code is horribly outdated (the book was released in 2009, so there's no excuse)- for example not using operator overloading instead of "Add" and "Multiply" static methods in a "Helper" class? No use of extension methods instead of the obligatory Helper classes to aid readibility? And there were a few cases where a hint of LINQ would make the code easier to read, more maintainable and potentially more efficient. Now I know this isnt a "Teach C#/LINQ/whatever book", its a "Teach Neural Nets" book, but to qualify it with "for C#" means you should be using appropriate language features, and not lazily porting line by line from a Java codebase.

    Add to that the formatting errors that appear all over the place (using Console.Writeline to output, then the example output appearing wrapped all on one line - not a major crime, but if you're *reading* the book as opposed to using it whilst running the code it is a problem), the flat out errors (creating a class called ErrorCalculation on one page, and from there on referring to it as CalculateError) mean that this book makes the subject (which is already complex) more difficult to follow due to the little errors.

    To add insult to injury, there is no source code CD, and visiting the authors website to get the source is much like reading the book - more difficult than it should be - the source code isn't under the "Source code" section that you'd expect. The source code provides a reasonable starting point, but as mentioned is simply a line by line Java port, so expect Java conventions (i.e. no new line for { which is the default in C# - a minor gripe I know, but if your writing for C# coders you probably want to follow C# guidelines).

    All in all, a reasonable book for an "Introduction to Neural Networks", but only an average book for an "Introduction to Neural Networks FOR C#".

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