Data Science (Record no. 47168)

MARC details
000 -LEADER
fixed length control field 02359 a2200205 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780262535434
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312 KEL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Kelleher, John D
245 ## - TITLE STATEMENT
Title Data Science
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge, Massachusetts
Name of publisher, distributor, etc The MIT Press
Date of publication, distribution, etc 2018
300 ## - PHYSICAL DESCRIPTION
Extent 264
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title The MIT Press Essential Knowledge Series
520 ## - SUMMARY, ETC.
Summary, etc 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.<br/>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.<br/>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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big Data
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Mining
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Quantitative Research
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Tierney, Brendan
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Dewey Decimal Classification

No items available.