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)

Don't Get Lost in Techniques – Focus on Optimizing Your Solutions

No matter how much we know, the key point remains being able to deliver an artificial intelligence solution or not. Implementing a machine learning (ML) or deep learning (DL) program remains difficult and will become more complex as technology progresses at exponential rates. This will be shown in Chapter 15, Cognitive NLP Chatbots, on quantum computing, which may revolutionize computing with its mind-blowing concepts. There is no such thing as a simple or easy way to design AI systems. A system is either efficient or not, beyond being either easy or not. Either the designed AI solution provides real-life practical uses or it builds up into a program that fails to work in various environments beyond the scope of training sets.

This chapter doesn't deal with how to build the most difficult system...