6 Mart 2024 Diğer Açık Erişim

Aslan, Ahmet

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  <identifier identifierType="DOI">10.48623/aperta.263730</identifier>
  <creators>
    <creator>
      <creatorName>Aslan, Ahmet</creatorName>
      <givenName>Ahmet</givenName>
      <familyName>Aslan</familyName>
    </creator>
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  <titles>
    <title>Understanding Long Short-Term Memory (Lstm) Networks: A Comprehensive Guide</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2024</publicationYear>
  <dates>
    <date dateType="Issued">2024-03-06</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Other</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/263730</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.48623/aperta.263729</relatedIdentifier>
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    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Long Short-Term Memory (LSTM) networks have emerged as a powerful tool in the realm of artificial intelligence and machine learning, particularly in tasks involving sequential data analysis, such as natural language processing, time series forecasting, and speech recognition. In this blog post, we will delve into the fundamentals of LSTM networks, explore their architecture, and discuss their applications in various domains.&lt;/p&gt;</description>
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