Neural Networks for Beginners (Secret of Data) by Thomas Laville
English | 2 Dec. 2017 | ISBN: 198137244X | ASIN: B077X21XRX | 112 Pages | AZW3 | 2.2 MB

Thinking of learning more Techniques and Algorithms in Artificial Neural Networks?

Then you have landed in the right place. The overall aim of this book in to give you an overview in the important concepts, methods and techniques used in the Artificial Neural Networks.

Artificial Neural Networks is generally referred as Neural Networks. This signal processing model is based on biological neural network. The theory test observations and later experiments of central nervous system of human brain system was the motivation to neural network. This literature is about basic neural network architectures and learning rules. Every effort has been made to present material in simple and regular manner so that it can be read and useful in no difficulty. In final chapters case studies are given to understand working of neural network.

There are many technologies available to data mining practitioners, including Artificial Neural Networks, Regression, and Decision Trees. Many practitioners are wary of Neural Networks due to their black box nature, even though they have proven themselves in many situations.

A Neural Networks is a complex architecture which consist a network of interconnected neurons, which is great alternative for complex problems when compared to conventional approach. It has covered fundamental concepts.

Since this literature is particularly written on Neural Networks, our choice of topics is guided by one standard. We want to present most useful picture of Neural Networks from simple to complex structure. The researchers from the different discipline are designing the Artificial Neural Networks to solve the problems of pattern recognition, prediction, optimization, associative memory and control.

Book Organisation

The organization of the book offers a great deal of flexibility for use in graduate level of neural network.

Introduction, History and Background of neural network.

Basic concepts to build Artificial Neural Networks.

Extensive Study on Artificial Neural Network Architecture.

Backpropagation Algorithm and its variant.

Others Networks Algorithms

Extensive literature covering every aspect of artificial neural network.

Book Objectives

The main purpose of this book is to provide the most fundamental knowledge on Artificial Neural Networks to the reader so that they can understand what the Artificial Neural Networks is all about.

This Book will help you:

To have an appreciation for Neural Networks and an understanding of their fundamental principles.

To have an elementary adeptness in a Neural Networks Concepts and terms which includes an ability to understand the algorithms.

To have some technical background in Neural Networks

Target Users

The book designed for a variety of target audiences. The most suitable users would include:

Newbies in Computer Science Techniques and Neural Networks

Professionals in Data scientist and Social Sciences

Professors or lecturers or tutors to be in position to find better ways to explain the content to their students with simples and easiest way

The students and Academicians, especially those that are focusing on Neural Networks and Deep Learning as their professions