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  <titleInfo>
    <title>Design of intelligent applications using machine learning and deep learning techniques</title>
  </titleInfo>
  <name type="personal">
    <namePart>Mangrulkar, Ramchandra S.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Michalas, Antonis</namePart>
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  <name type="personal">
    <namePart>Shekokar, Narendra M.</namePart>
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  </name>
  <name type="personal">
    <namePart>Narvekar, Meera</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Chavan, Pallavi V.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
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  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">flu</placeTerm>
    </place>
    <dateIssued encoding="marc">2022</dateIssued>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xiv, 432 pages : illustrations ; 26 cm.</extent>
  </physicalDescription>
  <tableOfContents>Data acquisition and preparation for artificial intelligence and machine learning -- Fundamental models in machine learning and deep learning -- Research aspects of machine learning: issues, challenges, and future scope -- Comprehensive analysis of dimensionality reduction techniques for machine learning applications -- Application pf deep learning in counting WBC's, RBCs, and blood platelets using faster region-based convolutional neural network -- Application of neural network and machine learning in mental health diagnosis -- Application of machine learning in cardiac arrhythmia -- Advances in machine learning and deep learning approaches for mammographic breast density measurement for breast cancer risk prediction: an overview -- Applications of machine learning psychology and the lifestyle disease diabetes -- Application of machine learning and deep learning in thyroid disease prediction -- Application of machine learning in fake news detection -- Authentication of broadcast news on social media using machine learning -- Application of deep learning in facial recognition -- Application of deep learning ion deforestation control and prediction -- Application of convolutional neural network in feather classifications -- Application of deep learning coupled with thermal imaging in detecting water stress in plants -- Machine learning techniques to classify breast cancer -- Application of deep learning in cartography using UNet and generative adversarial network -- Evaluation of intrusion detection system with rule-based technique to detect malicious web spiders using machine learning -- Application of machine learning to improve tourism industry -- Training agents to play 2D games using reinforcement learning -- Analysis of the effectiveness of the non-vaccine countermeasures taken by the Indian government against COVID-19 and forecasting using machine learning and deep -- Application of deep learning in video question answering system -- Implementation and analysis of machine learning and deep learning algorithms -- Comprehensive study of failed machine learning applications using a novel 3C approach.</tableOfContents>
  <note type="statement of responsibility">edited by Ramchandra S. Mangrulkar, [and 4 others].</note>
  <note>Includes bibliographical references and index.</note>
  <subject authority="lcsh">
    <topic>Machine learning</topic>
    <topic>Industrial applications</topic>
  </subject>
  <classification authority="lcc">Q325.5</classification>
  <classification authority="ddc">006.31 D460</classification>
  <identifier type="isbn">9780367679798</identifier>
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