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)

Implementation

This section shows how to use an advanced version of naive Bayes and where to insert this component in the CRLMM described in Chapter 11, Conceptual Representation Learning.

Gaussian naive Bayes

In implementation mode, a dataset with raw data from the blockchain will be used without the feature interpretation function of naive Bayes in the following table:

DAY STOCK BLOCKS DEMAND
10 1455 78 1
11 1666 67 1
12 1254 57 1
14 1563 45 1
15 1674 89 1
10 1465 89 1
12 1646 76 1
15 1746 87 2
12 1435 78 2

Each line represents a block:

  • DAY: The day of the month scanned (dd/mm/yyyy can be used beyond a prototype)
  • STOCK: The total inputs in a given location (A, B, or... F) found in the blocks and...