Preface

The second revision of Learning Data Mining with Python was written with the programmer in mind. It aims to introduce data mining to a wide range of programmers, as I feel that this is critically important to all those in the computer science field. Data mining is quickly becoming the building block of the next generation of Artificial Intelligence systems. Even if you don't find yourself building these systems, you will be using them, interfacing with them, and being guided by them. Understand the process behind them is important and helps you get the best out of them.
The second revision builds upon the first. Many of chapters and exercises are similar, although new concepts are introduced and exercises are expanded in scope. Those that had read the first revision should be able to move quickly through the book and pick up new knowledge along the way and engage with the extra activities proposed. Those new to the book are encouraged to take their time, do the exercises and experiment. Feel free to break the code to understand it, and reach out if you have any questions.
As this is a book aimed at programmers, we assume that you have some knowledge of programming and of Python itself. For this reason, there is little explanation of what the Python code itself is doing, except in cases where it is ambiguous.