Graph machine learning (Record no. 61093)

MARC details
000 -LEADER
fixed length control field 02599nam a22002777a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20231103130411.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231103b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781800204492
028 ## - DISTRIBUTOR NAME
Distributor Name : Technical Bureau
Distributor address : E/261, Shastri Nagar, Delhi.
Bill Number : TB2272
Bill Date : 27/10/2023
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31 STA
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Stamile, Claudio.
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name ; Deusebio, Enrico.
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name ; Marzullo, Aldo.
245 ## - TITLE STATEMENT
Title Graph machine learning
Remainder of title : take graph data to the next level by applying machine learning techniques and algorithms.
Statement of responsibility, etc /Claudio Stamile.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc , Birmingham
Name of publisher, distributor, etc : Packt Publishing Ltd.
Date of publication, distribution, etc , 2021.
300 ## - PHYSICAL DESCRIPTION
Extent xi, 338 p.
Dimensions : 26cm.
365 ## - TRADE PRICE
Price amount 3899
505 ## - FORMATTED CONTENTS NOTE
Contents note <br/>Getting Started with Graphs<br/>Graph Machine Learning<br/>Machine Learning on Graphs<br/>Unsupervised Graph Learning<br/>Supervised Graph Learning<br/>Problems with Machine Learning on Graphs<br/>Social Network Graphs<br/>Text Analytics and Natural Language Processing Using Graphs<br/>Graph Analysis for Credit Card Transactions<br/>Building a Data-Driven Graph-Powered Application<br/>Novel Trends on Graphs
520 ## - SUMMARY, ETC.
Summary, etc "Graph Machine Learning provides a new set of tools for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. You will start with a brief introduction to graph theory and graph machine learning, understanding their potential. As you proceed, you will become well versed with the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll then build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. Moving ahead, you will cover real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. Finally, you will learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, before progressing to explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications."
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Graph theory
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data processing
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Claudio Stamile
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Claudio Stamile.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Price effective from Koha item type
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 03/11/2023 Technical Bureau 3899.00 3 7 006.31 STA 29627 24/12/2025 15/05/2024 03/11/2023 Books

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