Machine Learning in Python : (Record no. 444)

000 -LEADER
fixed length control field 01364nam a22002777a 4500
003 - CONTROL NUMBER IDENTIFIER
control field BD-CoBAI
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20241030020002.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180924r20182015ii a b 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788126555925
040 ## - CATALOGING SOURCE
Original cataloging agency BD-CoBAI
Language of cataloging eng
Transcribing agency BD-CoBAI
Modifying agency BD-CoBAI
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
Item number B681m
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bowles, Michael,
Relator term author.
9 (RLIN) 1127
245 10 - TITLE STATEMENT
Title Machine Learning in Python :
Remainder of title essential techniques for predictive analysis /
Statement of responsibility, etc. Michael Bowles.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Indianapolis, IN :
-- New Delhi :
Name of publisher, distributor, etc. John Wiley & Sons, Inc.,
Date of publication, distribution, etc. c2015. [reprint 2018]
300 ## - PHYSICAL DESCRIPTION
Extent xxix, 326 pages :
Other physical details illustrations ;
Dimensions 24 cm
336 ## - CONTENT TYPE
Content type term text
Content type code txt
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
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note The two essential algorithms for making predictions -- Understand the problem by understanding the data -- Predictive model building : balancing performance, complexity, and big data -- Penalized linear regression -- Building predictive models using penalized linear methods -- Ensemble methods -- Building ensemble models with Python.
526 ## - STUDY PROGRAM INFORMATION NOTE
Program name Computer Science and Engineering CSE
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
9 (RLIN) 549
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Python (Computer program language)
9 (RLIN) 1128
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Python (Lenguaje de programación para computadora)
9 (RLIN) 2009
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Book
Koha issues (borrowed), all copies 10
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Source of acquisition Cost, normal purchase price Full call number Barcode Date last seen Copy number Price effective from Koha item type Total Checkouts Total Renewals Date last checked out
        Not For Loan BAIUST Library BAIUST Library General Stacks 2018-09-03 Purchased 772.00 006.31 B681m 010388 2018-09-24 1 2018-09-03 Book      
          BAIUST Library BAIUST Library General Stacks 2018-09-03 Purchased 772.00 006.31 B681m 010389 2023-07-27 2 2018-09-03 Book 5 5 2022-10-16
          BAIUST Library BAIUST Library General Stacks 2018-09-03 Purchased 772.00 006.31 B681m 010390 2024-11-21 3 2018-09-03 Book 5 1 2024-10-29

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