Book Image

Artificial Intelligence with Python - Second Edition

By : Prateek Joshi
Book Image

Artificial Intelligence with Python - Second Edition

By: Prateek Joshi

Overview of this book

Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.
Table of Contents (26 chapters)
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Constraint satisfaction problems

There are many problems that must be solved under constraints. These constraints are basically conditions that cannot be violated during the process of solving the problem.

These problems are referred to as Constraint Satisfaction Problems (CSPs).

To gain some intuitive understanding, let's quickly look at an example section of a Sudoku puzzle. Sudoku is a game where we cannot have the same number twice across a horizontal line, vertical line, or in the same square. Here is an example Sudoku board:

A black and silver text on a white surface  Description automatically generated

Figure 1: Example of a Sudoku board

Using constraint satisfaction and the rules of Sudoku we can quickly determine which numbers to try and which numbers not to try to solve the puzzle. For example, in this square:

Figure 2: Considering a problem in Sudoku

If we were not using CSP, one brute force approach would be to try all of the combinations of numbers in the slots and then check if the rules applied. For example, our...