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The Data Science Design Manual (Hardcover, 1st ed. 2017)
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The Data Science Design Manual (Hardcover, 1st ed. 2017)
Series: Texts in Computer Science
Expected to ship within 9 - 15 working days
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This engaging and clearly written textbook/reference provides a
must-have introduction to the rapidly emerging interdisciplinary
field of data science. It focuses on the principles fundamental to
becoming a good data scientist and the key skills needed to build
systems for collecting, analyzing, and interpreting data. The Data
Science Design Manual is a source of practical insights that
highlights what really matters in analyzing data, and provides an
intuitive understanding of how these core concepts can be used. The
book does not emphasize any particular programming language or
suite of data-analysis tools, focusing instead on high-level
discussion of important design principles. This easy-to-read text
ideally serves the needs of undergraduate and early graduate
students embarking on an "Introduction to Data Science" course. It
reveals how this discipline sits at the intersection of statistics,
computer science, and machine learning, with a distinct heft and
character of its own. Practitioners in these and related fields
will find this book perfect for self-study as well. Additional
learning tools: Contains "War Stories," offering perspectives on
how data science applies in the real world Includes "Homework
Problems," providing a wide range of exercises and projects for
self-study Provides a complete set of lecture slides and online
video lectures at www.data-manual.com Provides "Take-Home Lessons,"
emphasizing the big-picture concepts to learn from each chapter
Recommends exciting "Kaggle Challenges" from the online platform
Kaggle Highlights "False Starts," revealing the subtle reasons why
certain approaches fail Offers examples taken from the data science
television show "The Quant Shop" (www.quant-shop.com)
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