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  <titleInfo>
    <title>Industrial Applications of Machine Learning</title>
  </titleInfo>
  <name type="personal">
    <namePart>Larrañaga, Pedro</namePart>
    <role>
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    <role>
      <roleTerm type="text">author.</roleTerm>
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  <name type="personal">
    <namePart>Atienza, David</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Diaz-Rozo, Javier</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Ogbechie, Alberto</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Puerto-Santana, Carlos Esteban</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Bielza, Concha</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Taylor and Francis</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">bibliography</genre>
  <genre authority="">Electronic books.</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">flu</placeTerm>
    </place>
    <dateIssued encoding="marc">2018</dateIssued>
    <copyrightDate encoding="marc">2019</copyrightDate>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <extent>1 online resource (350 pages) : 148 illustrations, text file, PDF.</extent>
  </physicalDescription>
  <abstract>Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka.</abstract>
  <tableOfContents>1 The Fourth Industrial Revolution 2 Machine Learning  3 Applications of Machine Learning in Industrial Sectors  4 Component-Level Case Study: Remaining Useful Life of Bearings 5 Machine-Level Case Study: Fingerprint of Industrial Motors  6 Production-Level Case Study: Automated Visual Inspection of a Laser Process  7 Distribution-Level Case Study: Forecasting of Air Freight Delays.</tableOfContents>
  <note type="statement of responsibility">by Pedro Larrañaga, David Atienza, Javier Diaz-Rozo, Alberto Ogbechie, Carlos Esteban Puerto-Santana and Concha Bielza.</note>
  <note>Includes bibliographical references and index.</note>
  <note>Also available in print format.</note>
  <subject authority="lcsh">
    <topic>Machine learning</topic>
    <topic>Industrial applications</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>COMPUTERS / Database Management / Data Mining</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>COMPUTERS / Machine Theory</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>artificial intelligence</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>big data</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>data science</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>fourth industrial revoluntion</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>programming</topic>
  </subject>
  <classification authority="lcc">Q325.5</classification>
  <classification authority="ddc" edition="23">006.3/1</classification>
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  <relatedItem type="series">
    <titleInfo>
      <title>Chapman &amp; Hall/CRC Data Mining and Knowledge Discovery Series</title>
    </titleInfo>
  </relatedItem>
  <identifier type="isbn">9781351128384(e-book : PDF)</identifier>
  <identifier type="uri">https://www.taylorfrancis.com/books/9781351128384</identifier>
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    <url>https://www.taylorfrancis.com/books/9781351128384</url>
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    <recordCreationDate encoding="marc">190122</recordCreationDate>
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    <recordIdentifier source="FlBoTFG">9781351128384</recordIdentifier>
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