Idioma: Inglés
Publicado por LAP Lambert Academic Publishing, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
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Idioma: Inglés
Publicado por LAP Lambert Academic Publishing, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
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Idioma: Inglés
Publicado por Omniscriptum, LAP Lambert Academic Publishing, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Deep Learning Methods for Sentiment Analysis Using BERT & GRU Models' addresses the need for advanced sentiment analysis in financial markets, where traditional tools often fail to capture complex market emotions.This book presents deep learning techniques with Gated Recurrent Unit (GRU) and Bidirectional Encoder Representations from Transformers (BERT), offering enhanced analysis of sentiment patterns in financial data. It outlines a methodical approach involving data gathering, preprocessing, downsampling, and sentiment classification, using GRU and BERT for precise results.The book is ideal for finance, data science, and AI professionals, the book provides valuable insights to improve sentiment analysis, benefiting those engaged in financial market analysis, investment strategies, and natural language processing, and aims to enhance decision-making and strategic planning. 88 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Aug 2024, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Deep Learning Methods for Sentiment Analysis Using BERT & GRU Models' addresses the need for advanced sentiment analysis in financial markets, where traditional tools often fail to capture complex market emotions.This book presents deep learning techniques with Gated Recurrent Unit (GRU) and Bidirectional Encoder Representations from Transformers (BERT), offering enhanced analysis of sentiment patterns in financial data. It outlines a methodical approach involving data gathering, preprocessing, downsampling, and sentiment classification, using GRU and BERT for precise results.The book is ideal for finance, data science, and AI professionals, the book provides valuable insights to improve sentiment analysis, benefiting those engaged in financial market analysis, investment strategies, and natural language processing, and aims to enhance decision-making and strategic planning.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208012791 ISBN 13: 9786208012793
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 61,63
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Deep Learning Methods for Sentiment Analysis Using BERT & GRU Models' addresses the need for advanced sentiment analysis in financial markets, where traditional tools often fail to capture complex market emotions.This book presents deep learning techniques with Gated Recurrent Unit (GRU) and Bidirectional Encoder Representations from Transformers (BERT), offering enhanced analysis of sentiment patterns in financial data. It outlines a methodical approach involving data gathering, preprocessing, downsampling, and sentiment classification, using GRU and BERT for precise results.The book is ideal for finance, data science, and AI professionals, the book provides valuable insights to improve sentiment analysis, benefiting those engaged in financial market analysis, investment strategies, and natural language processing, and aims to enhance decision-making and strategic planning.