Large-scale data analytics with Python and Spark : (Record no. 46262)

MARC details
000 -LEADER
fixed length control field 02589nam a22003611i 4500
003 - CONTROL NUMBER IDENTIFIER
control field UkCbUP
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251203152134.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220614s2024||||enk ob 001 0|eng|d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781009318242
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9781009318259
041 ## - LANGUAGE CODE
Language English
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Edition number 23
Item number TRI
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Triguero, Isaac,
245 10 - TITLE STATEMENT
Title Large-scale data analytics with Python and Spark :
Remainder of title a hands-on guide to implementing machine learning solutions /
Statement of responsibility, etc Isaac Triguero, Mikel Galar.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc United Kingdom,
Name of publisher, distributor, etc Cambridge University Press, Cambridge,
Date of publication, distribution, etc 2024.
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 378 pages :
Other physical details illustrations ;
Dimensions 25 cm
505 ## - FORMATTED CONTENTS NOTE
Contents Introduction<br/>MapReduce<br/>Hadoop<br/>Spark<br/>Spark SQL and DataFrames<br/>Machine Learning with Spark<br/>Machine Learning for Big Data<br/>Implementing Classical Methods: k-Means and Linear Regression<br/>Advanced Examples: Semi-supervised, Ensembles, Deep Learning Model Deployment
520 ## - SUMMARY, ETC.
Summary, etc Based on the authors' extensive teaching experience, this hands-on graduate-level textbook teaches how to carry out large-scale data analytics and design machine learning solutions for big data. With a focus on fundamentals, this extensively class-tested textbook walks students through key principles and paradigms for working with large-scale data, frameworks for large-scale data analytics (Hadoop, Spark), and explains how to implement machine learning to exploit big data. It is unique in covering the principles that aspiring data scientists need to know, without detail that can overwhelm. Real-world examples, hands-on coding exercises and labs combine with exceptionally clear explanations to maximize student engagement. Well-defined learning objectives, exercises with online solutions for instructors, lecture slides, and an accompanying suite of lab exercises of increasing difficulty in Jupyter Notebooks offer a coherent and convenient teaching package. An ideal teaching resource for courses on large-scale data analytics with machine learning in computer/data science departments.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python (Computer program language)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big data.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Galar, Mikel,
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://ezproxy.lib.gla.ac.uk/login?url=https://doi.org/10.1017/9781009318242">https://ezproxy.lib.gla.ac.uk/login?url=https://doi.org/10.1017/9781009318242</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type General Books
100 1# - MAIN ENTRY--PERSONAL NAME
Relator term author.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
506 ## - RESTRICTIONS ON ACCESS NOTE
Terms governing access Access restricted to subscribing institutions.
630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title SPARK (Electronic resource)
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
International Standard Book Number 9781009318259.
856 40 - ELECTRONIC LOCATION AND ACCESS
Public note Connect to resource
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b41271294
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Location Shelving location Date of Cataloging Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non-fiction CUTN Central Library CUTN Central Library Generalia 03/12/2025   006.312 TRI 54750 03/12/2025 03/12/2025 General Books