Machine Learning for Beginners: (Record no. 11586)

MARC details
000 -LEADER
fixed length control field 01682nam a22002777i 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250819140058.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250807s2020 ii a|||fr|||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789389845426
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 b.h.m.
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bhasin, Harsh,
Relator term author.
9 (RLIN) 60102
245 10 - TITLE STATEMENT
Title Machine Learning for Beginners:
Remainder of title Learn to Build Machine Learning Systems Using Python /
Statement of responsibility, etc. Harsh Bhasin.
250 ## - EDITION STATEMENT
Edition statement first 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 244 pages :
Other physical details illustrations ;
Dimensions 23 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 feature selection techniques, classification algorithms, neural networks, PCA and appendix cheat sheets.<br/>
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Introduction to ML; Pre‑processing & Feature Selection; Regression; Classification (K‑NN, Logistic Regression, Naïve Bayes, LDA); Neural Networks I & II; SVM and Kernel Methods; Decision Trees; Clustering; Feature Extraction; Appendix (Cheat Sheets, Face Detection).<br/>
520 ## - SUMMARY, ETC.
Summary, etc. A hands-on guide to essential machine learning workflows using Python. Covers preprocessing, feature extraction, key classification algorithms, neural networks, SVMs, and clustering with practical examples. Aimed at undergraduate and postgraduate students and professionals entering ML via real-world implementations.turn0search2turn0search9turn0search5<br/>
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning
General subdivision introductory.
9 (RLIN) 61814
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data science
General subdivision machine learning.
9 (RLIN) 61815
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 09/01/2025   006.3 b.h.m MA0002225 09/01/2025 C.1 09/01/2025 Books