Algorithms For Dummies,
If you have a nagging curiosity about why an ad for that hammock you checked out on Amazon is appearing on your Facebook page, you'll find Algorithm for Dummies to be an enlightening introduction to this integral realm of math, science, and business. John Paul Mueller has produced 102 books and more than 600 articles to date on topics ranging from networking to machine learning. Luca Massaron is a data scientist specializing in organizing and interpreting big data and transforming it into smart data by means of the simplest and most effective data mining and machine learning techniques.
Algorithms For Dummies,
You need to learn about algorithms for school or work. Yet, all the books you've tried on the subject end up being more along the lines of really good sleep-inducing aids rather than texts to teach you something. Assuming that you can get past the arcane symbols obviously written by a demented two-year-old with a penchant for squiggles, you end up having no idea of why you'd even want to know anything about them. Most math texts are boring! However, Algorithms For Dummies is different. The first thing you'll note is that this book has a definite lack of odd symbols (especially of the squiggly sort) floating about. Yes, you see a few (it is a math book, after all), but what you find instead are clear instructions for using algorithms that actually have names and a history behind them to perform useful tasks. You'll encounter simple coding techniques that perform amazing things that will intrigue your friends and certainly make them jealous as you perform amazing feats of math that they can't begin to understand. You get all this without having to strain your brain, even a little, and you won't even fall asleep (well, unless you really want to do so).
About This Book
Algorithms For Dummies is the math book that you wanted in college but didn't get. You discover, for example, that algorithms aren't new. After all, the Babylonians used algorithms to perform simple tasks as early as 1,600 BC. If the Babylonians could figure this stuff out, certainly you can, too! This book actually has three things that you won't find in most math books:
Algorithms that have actual names and a historical basis so that you can remember the algorithm and know why someone took time to create it
Simple explanations of how the algorithm performs amazing feats of data manipulation, data analysis, or probability prediction
Code that shows how to use the algorithm without actually dealing with arcane symbols that no one without a math degree can understand
Part of the emphasis of this book is on using the right tools. This book uses Python to perform various tasks. Python has special features that make working with algorithms significantly easier. For example, Python provides access to a huge array of packages that let you do just about anything you can imagine, and more than a few that you can't. However, unlike many texts that use Python, this one doesn't bury you in packages. We use a select group of packages that provide great flexibility with a lot of functionality, but don't require you to pay anything. You can go through this entire book without forking over a cent of your hard-earned money.
You also discover some interesting techniques in this book. The most important is that you don't just see the algorithms used to perform tasks; you also get an explanation of how the algorithms work. Unlike many other books, Algorithms For Dummies enables you to fully understand what you're doing, but without requiring you to have a PhD in math. Every one of the examples shows the expected output and tells you why that output is important. You aren't left with the feeling that something is missing.
Of course, you might still be worried about the whole programming environment issue, and this book doesn't leave you in the dark there, either. At the beginning, you find complete installation instructions for Anaconda, which is the Python language Integrated Development Environment (IDE) used for this book. In addition, quick primers (with references) help you understand the basic Python programming that you need to perform. The emphasis is on getting you up and running as quickly as possible, and to make examples straightforward and simple so that the code doesn't become a stumbling block to learning.
To help you absorb the concepts, this book uses the following conventions:
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