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Doing data science / (Record no. 35323)

000 -LEADER
fixed length control field 01915cam a2200337Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field jomaaum
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220106104129.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130620t20142013caua 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781449358655 (pbk.)
International Standard Book Number 1449358659 (pbk.)
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
Item number O586
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (OCLC)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) QA76.9.D343
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) O545 2014
092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC)
Classification number 006.312
Item number One
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name O'Neil, Cathy,
Relator term author.
9 (RLIN) 44827
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Doing data science /
Statement of responsibility, etc Cathy O'Neil and Rachel Schutt.
246 1# - VARYING FORM OF TITLE
Display text Subtitle on cover:
Title proper/short title Straight talk from the frontline
260 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Sebastopol, CA :
Name of publisher, distributor, etc O'Reilly,
Date of publication, distribution, etc 2014.
300 ## - PHYSICAL DESCRIPTION
Extent xxv, 377 p. :
Other physical details ill. (col.) ;
Dimensions 23 cm.
500 ## - GENERAL NOTE
General note 2013-10-08: first release ; 2013-12-13: second release ; 2014-10-10: third release.
General note Includes index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction : What is data science? -- Statistical inference, exploratory data analysis, and the data science process -- Algorithms -- Spam filters, naive bayes, and wrangling -- Logistic regression -- Time stamps and financial modeling -- Extracting meaning from data -- Recommendation engines : building a user-facing data product at scale -- Data visualization and fraud detection -- Social networks and data journalism -- Causality -- Epidemiology -- Lessons learned from data competitions : data leakage and model evaluation -- Data engineering : MapReduce, Pregel, and Hadoop -- The students speak -- Next-generation data scientists, hubris, and ethics.
520 ## - SUMMARY, ETC.
Summary, etc A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
Topical term or geographic name as entry element Big data.
9 (RLIN) 42765
Topical term or geographic name as entry element Information science.
Topical term or geographic name as entry element Data structures (Computer science)
Topical term or geographic name as entry element Database management.
Topical term or geographic name as entry element Cyberinfrastructure.
9 (RLIN) 39735
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Schutt, Rachel,
Dates associated with a name 1976-
Relator term author.
9 (RLIN) 44828
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Lost status Withdrawn status Source of acquisition Cost, replacement price Damaged status Barcode Shelving location Current location Public note Full call number
2021-12-30AUM Main Library2021-12-30 2021-12-30 Book  UBCC33.06 AUM-024960English Collections HallAUM Main Libraryinvoice 2021/1473006.31 O586
2021-12-30AUM Main Library2021-12-30 2021-12-30 Book  UBCC33.06 AUM-024961English Collections HallAUM Main Libraryinvoice 2021/1473006.31 O586

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