Book Image

Hands-On Neural Network Programming with C#

By : Matt Cole
Book Image

Hands-On Neural Network Programming with C#

By: Matt Cole

Overview of this book

Neural networks have made a surprise comeback in the last few years and have brought tremendous innovation in the world of artificial intelligence. The goal of this book is to provide C# programmers with practical guidance in solving complex computational challenges using neural networks and C# libraries such as CNTK, and TensorFlowSharp. This book will take you on a step-by-step practical journey, covering everything from the mathematical and theoretical aspects of neural networks, to building your own deep neural networks into your applications with the C# and .NET frameworks. This book begins by giving you a quick refresher of neural networks. You will learn how to build a neural network from scratch using packages such as Encog, Aforge, and Accord. You will learn about various concepts and techniques, such as deep networks, perceptrons, optimization algorithms, convolutional networks, and autoencoders. You will learn ways to add intelligent features to your .NET apps, such as facial and motion detection, object detection and labeling, language understanding, knowledge, and intelligent search. Throughout this book, you will be working on interesting demonstrations that will make it easier to implement complex neural networks in your enterprise applications.
Table of Contents (16 chapters)
13
Activation Function Timings

Function minimization and maximization

Function minimization and maximization are the process of finding the smallest and largest value of a given function. Let's talk briefly about that value.

If the value is within a given range, then it is called the local extrema; if it is within the entire domain of a function then it is called the global extrema. Let's say we have a function f, and it's defined against a domain X. The maximum, or global, point at x* is f(x*) is greater than or equal to f(x) for all x in the domain X. Conversely, the function's global minimum point at x* is f(x*) is less than or equal to f(x) for all x in the domain X.

In a simpler fashion, the maximum point is also called the maximum value, and the minimum point is called the minimum value, of the function. The global maximum or minimum is either the highest or lowest function value in...