Machine Learning For Dummies. John Paul Mueller
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Introduction
The term machine learning has all sorts of meanings attached to it today, especially after Hollywood (and other movie studios) have gotten into the picture. Films such as Ex Machina have tantalized the imaginations of moviegoers the world over and made machine learning into all sorts of things that it really isn’t. Of course, most of us have to live in the real world, where machine learning actually does perform an incredible array of tasks that have nothing to do with androids that can pass the Turing Test (fooling their makers into believing they’re human). Machine Learning For Dummies, 2nd Edition gives you a view of machine learning in the real world and exposes you to the amazing feats you really can perform using this technology.
Even though the tasks that you perform using machine learning may seem a bit mundane when compared to the movie version, by the time you finish this book, you realize that these mundane tasks have the power to impact the lives of everyone on the planet in nearly every aspect of their daily lives. In short, machine learning is an incredible technology — just not in the way that some people have imagined.
This second edition of the book contains a significant number of changes, not the least of which is that it’s using pure Python code for the examples now upon request from our readers. You can still download R versions of every example, which is actually better than before when only some of the examples were available in R. In addition, the book contains new topics, including an entire chapter that discusses machine learning ethics.
About This Book
Machines and humans learn in entirely different ways, which is why the first part of this book is essential to your understanding of machine learning. Machines perform routine tasks at incredible speeds, but still require humans to do the actual thinking.
The second part of this book is about getting your system set up to use the various Python coding examples. The two setups work for desktop systems using Windows, Mac OS, or Linux, or mobile devices that have access to a Google Colab compatible browser.
The third part of the book discusses math basics with regard to machine learning requirements. It prepares you to perform math tasks associated with algorithms used in machine learning to make either predictions or classifications from your data.
The fourth part of the book helps you discover what to do about data that isn’t quite up to par. This part is also where you start learning about similarity and working with linear models. The most advanced chapter tells you how to work with ensembles of learners to perform tasks that might not otherwise be reasonable to complete.
The fifth part of the book is about practical application of machine learning techniques. You see how to do things like classify images, work with opinions and sentiments, and recommend products and movies.
The last part of the book contains helpful information to enhance your machine learning experience. This part of the book also contains a chapter specifically oriented toward ethical data use.
To make absorbing the concepts easy, this book uses the following conventions:
Text that you’re meant to type just as it appears in the book is in bold. The exception is when you’re working through a step list: Because each step is bold, the text to type is not bold.
Web addresses and programming code appear in monofont. If you're reading a digital version of this book on a device connected to the Internet, you can click or tap the web address to visit that website, like this: https://www.dummies.com.
When you need to type command sequences, you see them separated by a special arrow, like this: File ⇒ New File. In this example, you go to the File menu first and then select the New File entry on that menu.
When you see words in italics as part of a typing sequence, you need to replace that value with something that works for you. For example, if you see “Type Your Name and press Enter,” you need to replace Your Name with your actual name.
Foolish Assumptions
This book is designed for novice and professional alike. You can either read this book from cover to cover or look up topics and treat the book as a reference guide. However, we’ve made some assumptions about your level of knowledge when we put the book together. You should already know how to use your device and work with the operating system that supports it. You also know how to perform tasks like downloading files and installing applications. You can interact with Internet well enough to locate the resources you need to work with the book. You know how to work with archives, such as the .zip file format. Finally, a basic knowledge of math is helpful.
Icons Used in This Book
As you read this book, you see icons in the margins that indicate material of interest. This section briefly describes each icon.
