CHAPTER 1Introduction to Machine Learning

Welcome to Python Machine Learning! The fact that you are reading this book is a clear indication of your interest in this very interesting and exciting topic.

This book covers machine learning, one of the hottest programming topics in more recent years. Machine learning (ML) is a collection of algorithms and techniques used to design systems that learn from data. These systems are then able to perform predictions or deduce patterns from the supplied data.

With computing power increasing exponentially and prices decreasing simultaneously, there is no better time for machine learning. Machine learning tasks that usually require huge processing power are now possible on desktop machines. Nevertheless, machine learning is not for the faint of heart—it requires a good foundation in mathematics, statistics, as well as programming knowledge. The majority of the books in the market on machine learning go into too much detail, which often leaves beginning readers gasping for air. Most of the discussion on machine learning revolves heavily around statistical theories and algorithms, so unless you are a mathematician or a PhD candidate, you will likely find them difficult to digest. For most people, developers in particular, what they want is to have a foundational understanding of how machine learning works, and most importantly, how to apply machine learning in their applications. It is with this motive in mind that I set out to write this book. ...

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