Data science
(Book)
Author
Contributors
Tierney, Brendan, 1970- author.
Published
Cambridge, MA : The MIT Press, [2018].
Status
Copies
Location | Call Number | Status | Due Date |
---|---|---|---|
Shirlington - Adult Nonfiction | 006.312 KELLE | Checked Out | May 8, 2024 |
Shirlington - Adult Nonfiction | 006.312 KELLE | Checked Out | May 9, 2024 |
Description
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Published
Cambridge, MA : The MIT Press, [2018].
Format
Book
Physical Desc
xi, 244 pages : illustrations ; 18 cm.
Language
English
Notes
Bibliography
Includes bibliographical references and index.
Description
A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.
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Citations
APA Citation, 7th Edition (style guide)
Kelleher, J. D., & Tierney, B. (2018). Data science . The MIT Press.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Kelleher, John D., 1974- and Brendan Tierney. 2018. Data Science. The MIT Press.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Kelleher, John D., 1974- and Brendan Tierney. Data Science The MIT Press, 2018.
MLA Citation, 9th Edition (style guide)Kelleher, John D., and Brendan Tierney. Data Science The MIT Press, 2018.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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