Introduction to the Math of Neural Networks

Main
Mathematics - Computational Mathematics
Introduction to the Math of Neural...

Introduction to the Math of Neural Networks

Name: Introduction to the Math of Neural Networks
ISBN: 9781475190878

Jeff Heaton

3.0 / 1.5

4 comments

How much do you like this book?

What’s the quality of the file?

Download the book for quality assessment

What’s the quality of the downloaded files?

This book introduces the reader to the basic math used for neural network calculation. This book assumes the reader has only knowledge of college algebra and computer programming. This book begins by showing how to calculate output of a neural network and moves on to more advanced training methods such as backpropagation, resilient propagation and Levenberg Marquardt optimization. The mathematics needed by these techniques is also introduced. Mathematical topics covered by this book include first, second, Hessian matrices, gradient descent and partial derivatives. All mathematical notation introduced is explained. Neural networks covered include the feedforward neural network and the self organizing map. This book provides an ideal supplement to our other neural books. This book is ideal for the reader, without a formal mathematical background, that seeks a more mathematical description of neural networks.

Categories:

Mathematics - Computational Mathematics

Content Type:

Books

Year:

2012

Edition:

1st

Publisher:

Heaton Research

Language:

english