Advanced Deep Learning for Text and Image Sentiment Analysis (Paperback)
Language: English
Published by Pippet Sky, 2026
- Softcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
US$ 37.24
Quantity: 1 available
Add to basketItem description from seller
Paperback. Advanced Deep Learning for Text and Image Sentiment Analysis presents a focused technical treatment of deep learning methods for sentiment analysis across textual and visual data. The book examines how neural network architectures can extract meaningful patterns from language and images to support automated sentiment classification. It introduces core concepts in deep learning, text representation, image feature extraction, multimodal analysis, and sentiment modeling, with attention to computational challenges in processing heterogeneous data. The discussion connects natural language processing and computer vision with machine-learning approaches used to identify sentiment from written and visual content. Topics include feature learning, representation learning, neural-network classification, text sentiment analysis, image sentiment analysis, and evaluation for prediction systems. It provides references for readers on deep-learning techniques for sentiment analysis and multimodal data. A technical guide to deep learning methods for analyzing sentiment in text and images through advanced intelligent computational models. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9798240866654
- Title
- Advanced Deep Learning for Text and Image Sentiment Analysis (Paperback)
- Author
- Morenski
- Publisher
- Pippet Sky
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798240866654
Advanced Deep Learning for Text and Image Sentiment Analysis presents a focused technical treatment of deep learning methods for sentiment analysis across textual and visual data. The book examines how neural network architectures can extract meaningful patterns from language and images to support automated sentiment classification. It introduces core concepts in deep learning, text representation, image feature extraction, multimodal analysis, and sentiment modeling, with attention to computational challenges in processing heterogeneous data. The discussion connects natural language processing and computer vision with machine-learning approaches used to identify sentiment from written and visual content. Topics include feature learning, representation learning, neural-network classification, text sentiment analysis, image sentiment analysis, and evaluation for prediction systems. It provides references for readers on deep-learning techniques for sentiment analysis and multimodal data.
"Synopsis" may belong to another edition of this title.
CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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