Pragmatic machine learning with Python : (Record no. 11093)

MARC details
000 -LEADER
fixed length control field 01605nam a22002777i 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250723155432.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250723s2020 ii ao||fr|||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789389845365
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GaU‬‬
Transcribing agency EG-GaU‬‬
Modifying agency EG-GaU‬‬
Description conventions rda
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 006..3
Item number n.a.p.
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Nag, Avishek,
Relator term author.
9 (RLIN) 60495
245 10 - TITLE STATEMENT
Title Pragmatic machine learning with Python :
Remainder of title learn how to deploy machine learning models in production /
Statement of responsibility, etc. Avishek Nag.
250 ## - EDITION STATEMENT
Edition statement 1st edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New Delhi :
Name of producer, publisher, distributor, manufacturer BPB Publications,
Date of production, publication, distribution, manufacture, or copyright notice 2020.
300 ## - PHYSICAL DESCRIPTION
Extent 316 pages :
Other physical details illustrations ;
Dimensions 24 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references.<br/>
505 #0 - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction to ML & mathematical preliminaries ‡ 2. Classification ‡ 3. Regression ‡ 4. Clustering ‡ 5. Deep learning & neural networks ‡ 6. Miscellaneous unsupervised learning ‡ 7. Text mining ‡ 8. Machine learning models in production ‡ 9. Case studies & data science storytelling.<br/>
520 ## - SUMMARY, ETC.
Summary, etc. Balanced guide combining mathematical foundations with practical Python implementations. Covers supervised and unsupervised techniques, deep learning, text analytics, and strategies to deploy models in production-grade systems with PMML. ([Google Books, BPB Online, AbeBooks] :contentReference[oaicite:1]{index=1})<br/>
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning
General subdivision Study and teaching.
9 (RLIN) 60492
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning
General subdivision Implementation.
9 (RLIN) 60427
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
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 last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Media and mass communication Library Media and mass communication Library B4 08/19/2025   006.3 n.a.p MA0002258 08/19/2025 C.1 08/19/2025 Books