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A hands-on introduction to data science / Chirag Shah, Rutgers University, New Jersey.

By: Material type: TextTextDescription: pages cmISBN:
  • 9781108472449
Subject(s): Additional physical formats: Online version:: A hands-on introduction to data scienceLOC classification:
  • QA76.9 .S53 2020
Contents:
Conceptual introductions -- Tools for data science -- Machine learning for data science -- Applications, evaluations, and methods.
Summary: "This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science"--
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode
Books Books Zetech Library - Mang'u General Stacks Non-fiction QA76.9 .S53 2020 (Browse shelf(Opens below)) C.1 Available Z009648
Books Books Zetech Library - Mang'u General Stacks Non-fiction QA76.9 .S53 2020 (Browse shelf(Opens below)) C.2 Available Z009649
Books Books Zetech Library - Mang'u General Stacks Non-fiction QA76.9 .S53 2020 (Browse shelf(Opens below)) C3 Available z009977
Books Books Zetech Library - Mang'u General Stacks Non-fiction QA76.9 .S53 2020 (Browse shelf(Opens below)) C4 Available Z009978

Includes bibliographical references and index.

Conceptual introductions -- Tools for data science -- Machine learning for data science -- Applications, evaluations, and methods.

"This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science"--

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