Diğer Açık Erişim
Aslan, Ahmet
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Aslan, Ahmet</dc:creator> <dc:date>2024-03-06</dc:date> <dc:description>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.</dc:description> <dc:identifier>https://aperta.ulakbim.gov.trrecord/263730</dc:identifier> <dc:identifier>oai:aperta.ulakbim.gov.tr:263730</dc:identifier> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights> <dc:title>Understanding Long Short-Term Memory (LSTM) Networks: A Comprehensive Guide</dc:title> <dc:type>info:eu-repo/semantics/other</dc:type> <dc:type>publication-other</dc:type> </oai_dc:dc>
| Tüm sürümler | Bu sürüm | |
|---|---|---|
| Görüntülenme | 113 | 113 |
| İndirme | 137 | 137 |
| Veri hacmi | 15.0 MB | 15.0 MB |
| Tekil görüntülenme | 94 | 94 |
| Tekil indirme | 132 | 132 |