Download Ebook Code Your Own Neural Network: A step-by-step explanation, by Steven C. Shaffer
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Code Your Own Neural Network: A step-by-step explanation, by Steven C. Shaffer
Download Ebook Code Your Own Neural Network: A step-by-step explanation, by Steven C. Shaffer
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This mini-book will take you step-by-step through coding your own neural network. The language used is C++, although it’s really mostly C syntax. Once you have mastered the steps, it should be easy enough to translate your knowledge into most other languages.
The book goes step by step through the development of a relatively simple 3-layer back-propagation neural network to solve the exclusive OR problem. The purpose is to explain the concepts from a code-literate standpoint. There are lots of text-heavy and math-heavy explanations of how neural networks work, but few code-centric explanations. The exclusive OR problem is a good example because this cannot be solved with a single-layer neural network. If you are a coder, the explanations should make sense to you. No explanations of C++ syntax are given, so this is not for the novice programmer. This book is not for the purist or the researcher, it’s an introductory book for people who want a basic understanding of how neural networks work.
- Sales Rank: #162644 in eBooks
- Published on: 2015-02-22
- Released on: 2015-02-22
- Format: Kindle eBook
Most helpful customer reviews
21 of 22 people found the following review helpful.
Too many little things off-center to make it great
By Amazon Customer
I really looked forward to what is pretty much the first book that I found that is implementation focused, rather than theory focused, book on neural networks, and I really wanted to like it, but I just cannot. I've been playing with AI and Neural Networks for some time, and there's many good theory books but not many about what it takes to really implement a NN that works well. (I blogged a few things on my experiments in this space, but wanted to learn more from others)
This book is sadly not really an exception.
The book gives a very elementary introduction to coding the classical XOR network problem, but the code is at times beyond sloppy (like risking division by zero without even a basic check), and some basic things that could be done for readability (like a few simple functions for basic operations) aren't done. The narrative walks you through what it takes to build a NN, but only barely, and not really in an incremental way where you would have a program that does something useful after each step.
But beyond that, it goes totally flat in terms of suggesting improvements. With some very basic tweaks that are industry standard, you get a system that learns > 100x faster, but sadly the book doesn't even hint at those.
Also I found it strange in this time and age that the full program isn't just available for download somewhere, it's hard to cut-and-paste nicely (e.g. formatting/etc as used in programs) from a kindle book, so I basically had to retype the whole thing.
I hope the author is going to revise the book and his program, it does not take much to resolve most of the problems that stick out and turn this into a much better tutorial than it is right now.
5 of 5 people found the following review helpful.
Good Intro, So-So Code. Refer To My Git Repo For Python Implementation
By Richard Niemi
I thought this book was a great introduction to neural networks at a code level. By actually creating the thing I was able to get a decent understanding of how neural networks function and I can already see some areas I want to dig into deeper. I think that was the point of this book; to give an introduction to a hard topic and get the reader up to speed enough to be able to tackle a bigger project.
As other reviews have noted, the code style is pretty bad (the o as a loop variable actually tripped me up in my own code!) but the core idea is there and explained better than if you were to just go look at someone's implementation, so I think it was worth while. I actually translated this into python and did a little cleanup as I went. I've pushed my python version to a repo and you are welcome to refer to it at the link below if you would like.
https://github.com/Ricky-N/NeuralNetwork-XOR
7 of 8 people found the following review helpful.
Could be a good book, but needs some fixing
By Ben
I've become a little interested in AI as of late and though it would be good to toy around with making a Neural Network. After reading this book I can say that I understand the basic concepts of how to build one, but I can only give this book three stars. I wish that there was a little bit more meat to it (or some other sample problems we could make the Neural Network solve).
But my main issue has to be with the formatting of the code. While there are things in there that are legal in C++ (e.g. variables sharing the same name, but in different scopes), there are some bad programming practices used that undermine the clarity of the example. Another issue too is the font that was chosen to print the code. I cannot discern if something was a zero or an "O," character (many books I know use slashed zeros). It's even worse when the author used "o" as a variable name for a loop. The font choice wasn't good (Courier seems to be the standard for many programming books). I'd be willing to give this book four stars, but not with these problems.
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