John Paul Mueller - Data Science Programming All-In-One For Dummies

Data Science Programming All-in-One For Dummies

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Copyright 2020 by John Wiley & Sons, Inc., Hoboken, New Jersey

Published simultaneously in Canada

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Library of Congress Control Number: 2019954497

ISBN 978-1-119-62611-4;

ISBN 978-1-119-62613-8 (ebk); ISBN 978-1-119-62614-5 (ebk)

1. Chapter 2

1. Book 1 Chapter 1
2. Book 1 Chapter 2
3. Book 1 Chapter 3
4. Book 1 Chapter 5
5. Book 2 Chapter 3
6. Book 2 Chapter 4
7. Book 2 Chapter 6
8. Book 3 Chapter 1
9. Book 3 Chapter 2
10. Book 3 Chapter 3
11. Book 3 Chapter 4
12. Book 4 Chapter 1
13. Book 4 Chapter 2
14. Book 4 Chapter 3
15. Book 5 Chapter 2
16. Book 5 Chapter 3
17. Book 5 Chapter 4
18. Book 5 Chapter 5
19. Book 5 Chapter 6
20. Book 6 Chapter 2
21. Book 6 Chapter 3
22. Book 6 Chapter 4

Data science is a term that the media has chosen to minimize, obfuscate, and sometimes misuse. It involves a lot more than just data and the science of working with data. Today, the world uses data science in all sorts of ways that you might not know about, which is why you need Data Science Programming All-in-One For Dummies.

In the book, you start with both the data and the science of manipulating it, but then you go much further. In addition to seeing how to perform a wide range of analysis, you also delve into making recommendations, classifying real-world objects, analyzing audio, and even creating art.

However, you dont just learn about amazing new technologies and how to perform common tasks. This book also dispels myths created by people who wish data science were something different than it really is or who dont understand it at all. A great deal of misinformation swirls around the world today as the media seeks to sensationalize, anthropomorphize, and emotionalize technologies that are, in fact, quite mundane. Its hard to know what to believe. You find reports that robots are on the cusp of becoming sentient and that the giant tech companies can discover your innermost thoughts simply by reviewing your record of purchases. With this book, you can replace disinformation with solid facts, and you can use those facts to create a strategy for performing data science development tasks.

You might find that this book starts off a little slowly because most people dont have a good grasp on getting a system prepared for data science use. ) to make your coding efforts significantly easier and more focused on the data. In addition, in contrast to other environments, you dont actually write entire applications before you see something; you write code and focus on the results of just that code block as part of a whole application.

After you have a development environment installed and ready to use, you can start working with data in all its myriad forms in . This book covers a great many of these forms everything from in-memory datasets to those found on large websites. In addition, you see a number of data formats ranging from flat files to Relational Database Management Systems (RDBMSs) and Not Only SQL (NoSQL) databases.

Of course, manipulating data is worthwhile only if you can do something useful with it. discusses common sorts of analysis, such as linear and logistic regression, Bayes Theorem, and K-Nearest Neighbors (KNN).

Most data science books stop at this point. In this book, however, you discover AI, machine learning, and deep learning techniques to get more out of your data than you might have thought possible. This exciting part of the book, , represents the cutting edge of analysis. You use huge datasets to discover important information about large groups of people that will help you improve their health or sell them products.

Performing analysis may be interesting, but analysis is only a step along the path. shows you how to put your analysis to use in recommender systems, to classify objects, work with nontextual data like music and video, and display the results of an analysis in a form that everyone can appreciate.