Save 40% on books and eBooks in Engineering & Materials Science or in Social & Behavioral Sciences!

Texts in Computer Science

The Data Science Design Manual

Authors: Skiena, Steven S

Free Preview
  • Provides an introduction to data science, focusing on the fundamental skills and principles needed to build systems for collecting, analyzing, and interpreting data
  • Lays the groundwork of what really matters in analyzing data; ‘doing the simple things right’
  • Aids the reader in developing mathematical intuition, illustrating the key concepts with a minimum of formal mathematics
  • Highlights the core values of statistical reasoning using the approaches which come most naturally to computer scientists
see more benefits

Buy this book

eBook $54.99
price for USA in USD (gross)
valid through March 31, 2020
  • ISBN 978-3-319-55444-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $69.99
price for USA in USD
valid through March 31, 2020
  • ISBN 978-3-319-55443-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $69.99
price for USA in USD
valid through March 31, 2020
  • ISBN 978-3-319-85663-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

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)

About the authors

Dr. Steven S. Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University, with research interests in data science, natural language processing, and algorithms. He was awarded the IEEE Computer Science and Engineering Undergraduate Teaching Award “for outstanding contributions to undergraduate education ...and for influential textbooks and software.”  Dr. Skiena is the author of six books, including the popular Springer titles The Algorithm Design Manual and Programming Challenges: The Programming Contest Training Manual.

Reviews

“The book is more than a typical manual. In fact, the author himself designates it as a textbook for an introductory course on data science. The chapters are richly equipped with exercises. The topics are always explained starting with a proper motivation and continuing with practical examples. This is perhaps the most outstanding feature of the book. It can serve as a regular textbook for an academic course. In fact, I should like to recommend it exactly for this purpose. On the other hand, it provides a wealth of material for people from industry, such as software engineers, and can serve as a manual for them to accomplish data science tasks. It should be noted that the book is not just a text, but a much more complex product, including a full set of lecture slides available online as well as a solutions wiki.” (P. Navrat, Computing Reviews, February, 23, 2018)


Table of contents (13 chapters)

Table of contents (13 chapters)

Buy this book

eBook $54.99
price for USA in USD (gross)
valid through March 31, 2020
  • ISBN 978-3-319-55444-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $69.99
price for USA in USD
valid through March 31, 2020
  • ISBN 978-3-319-55443-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $69.99
price for USA in USD
valid through March 31, 2020
  • ISBN 978-3-319-85663-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
The Data Science Design Manual
Authors
Series Title
Texts in Computer Science
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
The Author(s)
eBook ISBN
978-3-319-55444-0
DOI
10.1007/978-3-319-55444-0
Hardcover ISBN
978-3-319-55443-3
Softcover ISBN
978-3-319-85663-6
Series ISSN
1868-0941
Edition Number
1
Number of Pages
XVII, 445
Number of Illustrations
43 b/w illustrations, 137 illustrations in colour
Topics