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  <titleInfo>
    <title>Physics of data science and machine learning</title>
  </titleInfo>
  <name type="personal">
    <namePart>Ijaz A Rauf</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">Boca Raton</placeTerm>
    </place>
    <publisher>CRC Press</publisher>
    <dateIssued>2025</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>xvi,194p. PB 23x15cm.</extent>
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  <abstract>Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, while exploring neural networks and machine learning, building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence.</abstract>
  <subject>
    <topic>Auxiliary Techniques and Procedures, Materials</topic>
  </subject>
  <classification authority="ddc" edition="23">530.0285 RAUP</classification>
  <identifier type="isbn">978103293937</identifier>
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