<?xml version="1.0" encoding="UTF-8"?>
<record
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd"
    xmlns="http://www.loc.gov/MARC21/slim">

  <leader>02599nam a22002777a 4500</leader>
  <controlfield tag="005">20231103130411.0</controlfield>
  <controlfield tag="008">231103b        |||||||| |||| 00| 0 eng d</controlfield>
  <datafield tag="020" ind1=" " ind2=" ">
    <subfield code="a">9781800204492</subfield>
  </datafield>
  <datafield tag="028" ind1=" " ind2=" ">
    <subfield code="a">: Technical Bureau</subfield>
    <subfield code="b">: E/261, Shastri Nagar, Delhi.</subfield>
    <subfield code="c">: TB2272</subfield>
    <subfield code="d">: 27/10/2023</subfield>
  </datafield>
  <datafield tag="082" ind1=" " ind2=" ">
    <subfield code="a">006.31 STA</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">Stamile, Claudio.</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">; Deusebio, Enrico.</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">; Marzullo, Aldo.</subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">Graph machine learning </subfield>
    <subfield code="b">: take graph data to the next level by applying machine learning techniques and algorithms.</subfield>
    <subfield code="c">/Claudio Stamile.</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="a">, Birmingham</subfield>
    <subfield code="b">: Packt Publishing Ltd.</subfield>
    <subfield code="c">, 2021.</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
    <subfield code="a">xi, 338 p.</subfield>
    <subfield code="c">: 26cm.</subfield>
  </datafield>
  <datafield tag="365" ind1=" " ind2=" ">
    <subfield code="b">3899</subfield>
  </datafield>
  <datafield tag="505" ind1=" " ind2=" ">
    <subfield code="a">
Getting Started with Graphs
Graph Machine Learning
Machine Learning on Graphs
Unsupervised Graph Learning
Supervised Graph Learning
Problems with Machine Learning on Graphs
Social Network Graphs
Text Analytics and Natural Language Processing Using Graphs
Graph Analysis for Credit Card Transactions
Building a Data-Driven Graph-Powered Application
Novel Trends on Graphs</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">"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."</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Machine learning</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Graph theory </subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Data processing</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2=" ">
    <subfield code="a">Claudio Stamile</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Claudio Stamile.</subfield>
  </datafield>
  <datafield tag="942" ind1=" " ind2=" ">
    <subfield code="c">BOOK</subfield>
  </datafield>
  <datafield tag="999" ind1=" " ind2=" ">
    <subfield code="c">61093</subfield>
    <subfield code="d">61093</subfield>
  </datafield>
  <datafield tag="952" ind1=" " ind2=" ">
    <subfield code="0">0</subfield>
    <subfield code="1">0</subfield>
    <subfield code="2">ddc</subfield>
    <subfield code="4">0</subfield>
    <subfield code="7">0</subfield>
    <subfield code="a">SNUL</subfield>
    <subfield code="b">SNUL</subfield>
    <subfield code="d">2023-11-03</subfield>
    <subfield code="e">Technical Bureau </subfield>
    <subfield code="g">3899.00</subfield>
    <subfield code="l">3</subfield>
    <subfield code="m">7</subfield>
    <subfield code="o">006.31 STA</subfield>
    <subfield code="p">29627</subfield>
    <subfield code="r">2025-12-24 12:29:32</subfield>
    <subfield code="s">2024-05-15</subfield>
    <subfield code="w">2023-11-03</subfield>
    <subfield code="y">BOOK</subfield>
  </datafield>
</record>
