Algorithms For Dummies. John Paul Mueller

have to rely on other sources to provide the definitions you need.

       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 the live link to visit that website, like this: http://www.dummies.com.

       When you need to click command sequences, you see them separated by a special arrow, like this: File ⇒ New File, which tells you to click File and then New File.

Foolish Assumptions

      You might find it difficult to believe that we’ve assumed anything about you — after all, we haven’t even met you yet! Although most assumptions are indeed foolish, we made certain assumptions to provide a starting point for the book.

      The first assumption is that you’re familiar with the platform you want to use, because the book doesn’t provide any guidance in this regard. (Chapter 3 does, however, tell you how to access Google Colab from your browser and use it to work with the code examples in the book.) To give you the maximum information about Python with regard to algorithms, this book doesn’t discuss any platform-specific issues. You really do need to know how to install applications, use applications, and generally work with your chosen platform before you begin working with this book.

      This book isn’t a math primer. Yes, you see lots of examples of complex math, but the emphasis is on helping you use Python to perform common tasks using algorithms rather than learning math theory. However, you do get explanations of many of the algorithms used in the book so that you can understand how the algorithms work. Chapters 1 and 2 guide you through a what you need to know in order to use this book successfully. Chapter 5 is a special chapter that discusses how to create your own math library, which significantly aids you in understanding how math works with code to create a reusable package. It also looks dandy on your resume to say that you’ve created your own math library.

      This book also assumes that you can access items on the Internet. Sprinkled throughout are numerous references to online material that will enhance your learning experience. However, these added sources are useful only if you actually find and use them. You must also have Internet access to use Google Colab.

Icons Used in This Book

      As you read this book, you encounter icons in the margins that indicate material of interest (or not, as the case may be). Here’s what the icons mean:

      

Tips are nice because they help you save time or perform some task without a lot of extra work. The tips in this book are time-saving techniques or pointers to resources that you should try so that you can get the maximum benefit from Python, or in performing algorithm-related or data analysis–related tasks.

We don’t want to sound like angry parents or some kind of maniacs, but you should avoid doing anything that’s marked with a Warning icon. Otherwise, you might find that your application fails to work as expected, you get incorrect answers from seemingly bulletproof algorithms, or (in the worst-case scenario) you lose data.

      

Whenever you see this icon, think advanced tip or technique. You might find these tidbits of useful information just too boring for words, or they could contain the solution you need to get a program running. Skip these bits of information whenever you like.

      

If you don’t get anything else out of a particular chapter or section, remember the material marked by this icon. This text usually contains an essential process or a bit of information that you must know to work with Python, or to perform algorithm-related or data analysis–related tasks successfully.

Beyond the Book

      This book isn’t the end of your Python or algorithm learning experience — it’s really just the beginning. We provide online content to make this book more flexible and better able to meet your needs. That way, as we receive email from you, we can address questions and tell you how updates to Python, or its associated add-ons affect book content. In fact, you gain access to all these cool additions:

       Cheat sheet: You remember using crib notes in school to make a better mark on a test, don’t you? You do? Well, a cheat sheet is sort of like that. It provides you with some special notes about tasks that you can do with Python, Google Colab, and algorithms that not every other person knows. To find the cheat sheet for this book, go to www.dummies.com and enter Algorithms For Dummies, 2nd Edition Cheat Sheet in the search box. The cheat sheet contains really neat information such as finding the algorithms that you commonly need to perform specific tasks.

       Updates: Sometimes changes happen. For example, we might not have seen an upcoming change when we looked into our crystal ball during the writing of this book. In the past, this possibility simply meant that the book became outdated and less useful, but you can now find updates to the book, if we make any, by going to www.dummies.com and entering Algorithms For Dummies, 2nd Edition in the search box.In addition to these updates, check out the blog posts with answers to reader questions and demonstrations of useful book-related techniques at http://blog.johnmuellerbooks.com/.

       Companion files: Hey! Who really wants to type all the code in the book and reconstruct all those plots manually? Most readers prefer to spend their time actually working with Python, performing tasks using algorithms, and seeing the interesting things they can do, rather than typing. Fortunately for you, the examples used in the book are available for download, so all you need to do is read the book to learn algorithm usage techniques. You can find these files by searching Algorithms For Dummies, 2nd Edition at www.dummies.com and scrolling down the left side of the page that opens. The source code is also at http://www.johnmuellerbooks.com/source-code/, and https://github.com/lmassaron/algo4d_2ed.

Where to Go from Here

      It’s time to start your algorithm learning adventure! If you’re completely new to algorithms, you should start with Chapter 1 and progress through the book at a pace that allows you to absorb as much of the material as possible. Make sure to read about Python, because the book uses this language as needed for the examples.

      If you’re a novice who’s in an absolute rush to get going with algorithms as quickly as possible, you can skip to Chapter 3 with the understanding that you may find some topics a bit confusing later.

      Readers who have some exposure to Python, and have the appropriate language versions installed, can save reading time by moving directly to Chapter 5. You can always go back to earlier chapters as necessary when you have questions. However, you