Book Image

Mastering Python 2E - Second Edition

By : Rick van Hattem
5 (1)
Book Image

Mastering Python 2E - Second Edition

5 (1)
By: Rick van Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
19
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20
Index

Introduction to artificial intelligence

Before we continue with this chapter, we need to establish a few definitions. Because artificial intelligence (AI) is such a broad subject, the lines tend to blur a bit, so we need to make sure that we are all talking about the same thing.

First of all, we define AI as any algorithm with a human-like ability to solve problems. While I admit that this statement is very broad, any narrower definition would exclude valid AI strategies. What is and is not AI is more a philosophical question than a technical one. While (almost) anyone would consider a neural network to be AI, once you get to algorithms such as (Bayesian) decision trees, not everyone agrees anymore.

With that broad definition in mind, here is a list of technologies and terms we are going to cover, with a short explanation of what they are and what they can do.

Types of AI

Within the broad scope of AI, we have two major branches, machine learning (ML) and the rest....