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      Published by: John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030-5774, www.wiley.com

      Copyright © 2021 by John Wiley & Sons, Inc., Hoboken, New Jersey

      Published simultaneously in Canada

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      Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com.

      Library of Congress Control Number: 2021944259

      ISBN 978-1-119-81155-8 (pbk); ISBN 978-1-119-81166-4 (ebk); ISBN 978-1-119-81161-9 (ebk)

      Data Science For Dummies®

      To view this book's Cheat Sheet, simply go to www.dummies.com and search for “Data Science For Dummies Cheat Sheet” in the Search box.

      Table of Contents

      1  Cover

      2  Title Page

      3  Copyright

      4  Introduction About This Book Foolish Assumptions Icons Used in This Book Beyond the Book Where to Go from Here

      5  Part 1: Getting Started with Data Science Chapter 1: Wrapping Your Head Around Data Science Seeing Who Can Make Use of Data Science Inspecting the Pieces of the Data Science Puzzle Exploring Career Alternatives That Involve Data Science Chapter 2: Tapping into Critical Aspects of Data Engineering Defining Big Data and the Three Vs Identifying Important Data Sources Grasping the Differences among Data Approaches Storing and Processing Data for Data Science

      6  Part 2: Using Data Science to Extract Meaning from Your Data Chapter 3: Machine Learning Means … Using a Machine to Learn from Data Defining Machine Learning and Its Processes Considering Learning Styles Seeing What You Can Do Chapter 4: Math, Probability, and Statistical Modeling Exploring Probability and Inferential Statistics Quantifying Correlation Reducing Data Dimensionality with Linear Algebra Modeling Decisions with Multiple Criteria Decision-Making Introducing Regression Methods Detecting Outliers Introducing Time Series Analysis Chapter 5: Grouping Your Way into Accurate Predictions Starting with Clustering Basics Identifying


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