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Data science / John D. Kelleher and Brendan Tierney.

By: Kelleher, John D, 1974- [author.].
Contributor(s): Tierney, Brendan, 1970- [author.] | IEEE Xplore (Online Service) [distributor.] | MIT Press [publisher.].
Material type: materialTypeLabelBookSeries: MIT Press essential knowledge series: Publisher: Cambridge, Massachusetts : The MIT Press, [2018]Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2018]Description: 1 PDF (xi, 264 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9780262347020.Subject(s): Big data | Machine learning | Data mining | Quantitative research | Big data | Data mining | Machine learning | Quantitative researchGenre/Form: Electronic books.Additional physical formats: Print version:: Data science.DDC classification: 005.7 Online resources: Abstract with links to resource Also available in print.
Contents:
What is data science? -- What is data and what is a dataset? -- The data science ecosystem -- Machine learning 101 -- Standard data science tasks -- Privacy and ethics -- Future trends and principles of success.
Summary: 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.
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Includes bibliographical references and index.

What is data science? -- What is data and what is a dataset? -- The data science ecosystem -- Machine learning 101 -- Standard data science tasks -- Privacy and ethics -- Future trends and principles of success.

Restricted to subscribers or individual electronic text purchasers.

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.

Also available in print.

Mode of access: World Wide Web

Print version record.

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