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)

Chapter 10 – Applying Biomimicking to AI

1. Deep learning and machine learning mean the same thing. (Yes | No)

No. When an AI program contains a network, especially a deep one (with several layers), that is deep learning. Deep learning is a subset of machine learning.

When programs such as an Markov Decision Process (MDP) are used, that is machine learning.

To sum it up, not all artificial intelligence programs have to learn. Machine learning is a subset of artificial intelligence programs that learn but do not require networks. Deep learning is a subset of machine learning that uses networks.

2. Deep learning networks mostly reproduce human brain functions. (Yes | No)

Yes in neuroscience research on the human brain. Computer models of the brain using deep learning can provide interesting models.

Sometimes yes, when deep learning networks try to reproduce human vision...