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  <titleInfo>
    <title>Fundamentals of data science</title>
  </titleInfo>
  <name type="personal">
    <namePart>Wagh, Sanjeev</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Bhende, Manisha</namePart>
  </name>
  <name type="personal">
    <namePart>Thakare, Anuradha</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
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  <originInfo>
    <place>
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    </place>
    <dateIssued encoding="marc">2022</dateIssued>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>1 online resource (xiv, 282 pages)</extent>
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  <abstract>Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes Readers will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue. This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge. Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.</abstract>
  <note type="statement of responsibility">Sanjeev J. Wagh, Manisha S. Bhende, and Anuradha D. Thakare.</note>
  <note>"A Chapman &amp; Hall book."</note>
  <subject authority="lcsh">
    <topic>Databases</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Information retrieval</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Data mining</topic>
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  <subject authority="lcsh">
    <topic>Machine learning</topic>
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  <subject authority="rvm">
    <topic>Recherche de l'information</topic>
  </subject>
  <subject authority="rvm">
    <topic>Exploration de données (Informatique)</topic>
  </subject>
  <subject authority="rvm">
    <topic>Apprentissage automatique</topic>
  </subject>
  <subject authority="">
    <topic>information retrieval</topic>
  </subject>
  <subject authority="">
    <topic>BUSINESS &amp; ECONOMICS</topic>
    <topic>Statistics</topic>
  </subject>
  <subject authority="">
    <topic>COMPUTERS</topic>
    <topic>Computer Graphics</topic>
    <topic>Game Programming &amp; Design</topic>
  </subject>
  <subject authority="">
    <topic>COMPUTERS</topic>
    <topic>Database Management</topic>
    <topic>General</topic>
  </subject>
  <subject authority="">
    <topic>Data mining</topic>
  </subject>
  <subject authority="">
    <topic>Databases</topic>
  </subject>
  <subject authority="">
    <topic>Information retrieval</topic>
  </subject>
  <subject authority="">
    <topic>Machine learning</topic>
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  <classification authority="lcc">QA76.9 .D3 2022</classification>
  <classification authority="ddc">005.74</classification>
  <identifier type="isbn">9780429443237</identifier>
  <identifier type="isbn">0429443234</identifier>
  <identifier type="isbn">9780429811470</identifier>
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  <identifier type="isbn">0429811462</identifier>
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