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  <titleInfo>
    <title>Mathematical foundations for data analysis</title>
  </titleInfo>
  <name type="personal">
    <namePart>Phillips, Jeff M.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">Cham</placeTerm>
    </place>
    <publisher>Springer Nature Singapore Pte Ltd.</publisher>
    <dateIssued>2021</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <physicalDescription>
    <extent>xvii, 287 p. : ill., Col. ; 24 cm</extent>
  </physicalDescription>
  <tableOfContents>1. Probability Review
2. Convergence and Sampling
3. Linear Algebra Review
4. Distances and Nearest Neighbors
5. Linear Regression
6. Gradient Descent
7. Dimensionality Reduction
8. Clustering
9. Classification
10. Graph structured data
11. Big data and sketching
Index</tableOfContents>
  <note>Includes bibliographical references and indexes.</note>
  <subject>
    <topic>Mathematics</topic>
    <topic>Quantitative research Mathematics</topic>
    <topic>Machine learning Mathematics</topic>
    <topic>Data mining Mathematics</topic>
    <topic>Linear Algebra</topic>
    <topic>Data analysis</topic>
    <topic>Visualization</topic>
    <topic>FC</topic>
  </subject>
  <classification authority="ddc">006.3120151 PHI</classification>
  <identifier type="isbn">9783030623401 (hb)</identifier>
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