Essential math for data science [electronic resources] : (Record no. 2415)

MARC details
000 -LEADER
fixed length control field 03419cam a22005537i 4500
001 - CONTROL NUMBER
control field 23168451
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250909142149.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230602s2022 cc 001 0 eng d
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2023276388
015 ## - NATIONAL BIBLIOGRAPHY NUMBER
National bibliography number GBC290257
Source bnb
016 7# - NATIONAL BIBLIOGRAPHIC AGENCY CONTROL NUMBER
Record control number 020621576
Source Uk
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789355422743
Qualifying information paperback
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Qualifying information paperback
035 ## - SYSTEM CONTROL NUMBER
System control number 23168451
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1328015167
040 ## - CATALOGING SOURCE
Original cataloging agency UKMGB
Language of cataloging eng
Description conventions rda
Transcribing agency UKMGB
Modifying agency FIE
-- OCLCF
-- UAP
-- NVC
-- JRZ
-- OCL
-- VNVGU
-- DLC
042 ## - AUTHENTICATION CODE
Authentication code lccopycat
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.D343
Item number N54 2022
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31 NIE
Edition number 23
092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC)
Edition number 0
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Nield, Thomas
Titles and words associated with a name (Computer programmer),
Relator term author.
245 10 - TITLE STATEMENT
Title Essential math for data science [electronic resources] :
Remainder of title take control of your data with fundamental linear algebra, probability, and statistics /
Statement of responsibility, etc. Thomas Nield.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Beijing ;
-- Boston :
Name of producer, publisher, distributor, manufacturer O'Reilly,
Date of production, publication, distribution, manufacture, or copyright notice 2022.
300 ## - PHYSICAL DESCRIPTION
Extent 1 digital resource (xiv, 332 pages) ;
Dimensions 24 cm
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
336 ## - CONTENT TYPE
Content type term still image
Content type code sti
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
500 ## - GENERAL NOTE
General note Includes index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Basic math and calculus review -- Probability -- Descriptive and inferential statistics -- Linear algebra -- Linear regression -- Logistic regression and classification -- Neural networks -- Career advice and the path forward.
520 ## - SUMMARY, ETC.
Summary, etc. To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need in data science, including probability, statistics, hypothesis testing, linear algebra, machine learning, and calculus. Practical examples with Python code will help you see how the math applies to the work you'll be doing, providing a clear understanding of how concepts work under the hood while connecting them to applications like machine learning. You'll get a solid foundation in the math essential for data science, but more importantly, you'll be able to use it to: Recognize the nuances and pitfalls of probability math Master statistics and hypothesis testing (and avoid common pitfalls) Discover practical applications of probability, statistics, calculus, and machine learning Intuitively understand linear algebra as a transformation of space, not just grids of numbers being multiplied and added Perform calculus derivatives and integrals completely from scratch in Python Apply what you've learned to machine learning, including linear regression, logistic regression, and neural networks --
Assigning source Provided by publisher.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data mining
General subdivision Mathematics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning
General subdivision Mathematics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Mathematical statistics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer science
General subdivision Mathematics.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer science
General subdivision Mathematics.
Source of heading or term fast
Authority record control number or standard number (OCoLC)fst00872460
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data mining
General subdivision Mathematics.
Source of heading or term fast
Authority record control number or standard number (OCoLC)fst02013374
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Mathematical statistics.
Source of heading or term fast
Authority record control number or standard number (OCoLC)fst01012127
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
Source of heading or term fast
Authority record control number or standard number (OCoLC)fst01077737
655 #7 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Handbooks and manuals.
Source of term fast
Authority record control number or standard number (OCoLC)fst01423877
655 #7 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Handbooks and manuals.
Source of term lcgft
887 ## - NON-MARC INFORMATION FIELD
Source of data CamTech Library
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c copycat
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e ncip
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date due Date last seen Date last checked out Copy number Price effective from Koha item type
    Dewey Decimal Classification     CamTech Library CamTech Library FaE's Corner, Faculty of Engineering 09/09/2025 1 006.31 NIE 0000002873 09/25/2025 09/11/2025 09/11/2025 C.1 09/09/2025 Books

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