The data science handbook (Record no. 1813)

MARC details
000 -LEADER
fixed length control field 02731nam a2200229 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250804170940.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250804b2025|||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781394234516
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Cady, Field
Relator term Author
245 ## - TITLE STATEMENT
Title The data science handbook
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New Jersey:
Name of publisher Wiley Data and Cybersecurity,
Year of publication 2025.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xix, 347p.
500 ## - GENERAL NOTE
General note Practical, accessible guide to becoming a data scientist, updated to include the latest advances in data science and related fields.<br/><br/>Becoming a data scientist is hard. The job focuses on mathematical tools, but also demands fluency with software engineering, understanding of a business situation, and deep understanding of the data itself. This book provides a crash course in data science, combining all the necessary skills into a unified discipline.<br/><br/>The focus of The Data Science Handbook is on practical applications and the ability to solve real problems, rather than theoretical formalisms that are rarely needed in practice. Among its key points are:<br/><br/>An emphasis on software engineering and coding skills, which play a significant role in most real data science problems.<br/>Extensive sample code, detailed discussions of important libraries, and a solid grounding in core concepts from computer science (computer architecture, runtime complexity, and programming paradigms).<br/>A broad overview of important mathematical tools, including classical techniques in statistics, stochastic modeling, regression, numerical optimization, and more.<br/>Extensive tips about the practical realities of working as a data scientist, including understanding related jobs functions, project life cycles, and the varying roles of data science in an organization.<br/>Exactly the right amount of theory. A solid conceptual foundation is required for fitting the right model to a business problem, understanding a tool’s limitations, and reasoning about discoveries.<br/>Data science is a quickly evolving field, and this 2nd edition has been updated to reflect the latest developments, including the revolution in AI that has come from Large Language Models and the growth of ML Engineering as its own discipline. Much of data science has become a skillset that anybody can have, making this book not only for aspiring data scientists, but also for professionals in other fields who want to use analytics as a force multiplier in their organization.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Programming Language Concepts
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Performance and Computer Memory
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer Memory and Data Structures
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://ieeexplore.ieee.org/servlet/opac?bknumber=10766879
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Shelving location Coded location qualifier Full call number Accession Number Koha item type
        Dr. S. R. Ranganathan Library Dr. S. R. Ranganathan Library Ebook (Online Access) --- 005.74 EB0237 e-Books

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