Book Image

Artificial Intelligence By Example

By : Denis Rothman
Book Image

Artificial Intelligence By Example

By: Denis Rothman

Overview of this book

Artificial intelligence has the potential to replicate humans in every field. Artificial Intelligence By Example serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, you will have understood the fundamentals of AI and worked through a number of case studies that will help you develop your business vision.
Table of Contents (19 chapters)

Become an Unconventional Innovator

In corporate projects, there always comes the point when a problem that seems impossible to solve hits you. At that point, you try everything you learned, but it doesn't work for what's asked of you. Your team or customer begins to look elsewhere. It's time to react.

In this chapter, an impossible-to-solve business case regarding material optimization will be implemented successfully with an example of a feedforward neural network (FNN) with backpropagation.

Feedforward networks are the building blocks of deep learning. The battle around the XOR function perfectly illustrates how deep learning regained popularity in corporate environments. The XOR FNN illustrates one of the critical functions of neural networks: classification. Once information becomes classified into subsets, it opens the doors to prediction and many other functions...