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 Title Exploring Data Science
 Author(s) Nina Zumel and John Mount
 Publisher: Manning Publishing
 Hardcover/Paperback N/A
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 Language: English
 ISBN10/ASIN: N/A
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Book Description
This book introduces readers to various areas in data science and explains which methodologies work best for each, with practical examples in R, Python, and other languages.
There's never been a better time to get into data science. But where do you start? Data Science is a broad field, incorporating aspects of statistics, machine learning, and data engineering. It's easy to become overwhelmed, or end up learning about a small section of data science or a single methodology.
Exploring Data Science is a collection of five handpicked chapters introducing you to various areas in data science and explaining which methodologies work best for each. John Mount and Nina Zumel, authors of Practical Data Science with R, selected these chapters to give you the big picture of the many data domains. You’ll learn about time series, neural networks, text analytics, and more. As you explore different modeling practices, you’ll see practical examples of how R, Python, and other languages are used in data science. Along the way, you'll experience a sample of Manning books you may want to add to your library.
About the Authors Nina Zumel and John Mount are cofounders of a San Franciscobased data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science at winvector.com.
 Data Science
 Data Analysis and Data Mining, Big Data
 The R Programming Language
 Statistics, Mathematical Statistics, and SAS Programming
 R for Data Science: Visualize, Model, Transform, Tidy, and Import Data
 The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists
 Introduction to Data Science (Jeffrey Stanton)
 Data Mining and Analysis: Fundamental Concepts and Algorithms
 A Programmer's Guide to Data Mining (Ron Zacharski)




















