ISBN: 9786630478556 - advanced nlp with deep and quantum machine learning (10 risultati)

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Paperback. Condizione: new. Paperback. Deep and Quantum Learning for NLP explores the emerging intersection of Natural Language Processing and Quantum Machine Learning, focusing on the use of Quantum Convolutional Neural Networks (QCNNs) for sentiment analysis.The book provides a progressive introduction to the foundations of NLP, quantum computing, and Quantum Machine Learning before examining the application of QCNNs to text classification. Particular attention is given to the role of textual representation and the impact of widely used word embedding techniques, including Word2Vec, GloVe, FastText, and BERT, on QCNN-based sentiment analysis.By combining theoretical concepts with experimental investigation, this book offers a perspective on how classical language representations can be integrated with quantum learning architectures. It also discusses the current challenges and limitations of quantum NLP and highlights promising directions for future research.This book is intended for researchers, postgraduate students, and practitioners interested in NLP, quantum computing, quantum machine learning, and the emerging field of Quantum Natural Language Processing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 96 pp. Englisch.

Paperback. Condizione: new. Paperback. Deep and Quantum Learning for NLP explores the emerging intersection of Natural Language Processing and Quantum Machine Learning, focusing on the use of Quantum Convolutional Neural Networks (QCNNs) for sentiment analysis.The book provides a progressive introduction to the foundations of NLP, quantum computing, and Quantum Machine Learning before examining the application of QCNNs to text classification. Particular attention is given to the role of textual representation and the impact of widely used word embedding techniques, including Word2Vec, GloVe, FastText, and BERT, on QCNN-based sentiment analysis.By combining theoretical concepts with experimental investigation, this book offers a perspective on how classical language representations can be integrated with quantum learning architectures. It also discusses the current challenges and limitations of quantum NLP and highlights promising directions for future research.This book is intended for researchers, postgraduate students, and practitioners interested in NLP, quantum computing, quantum machine learning, and the emerging field of Quantum Natural Language Processing. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Deep and Quantum Learning for NLP explores the emerging intersection of Natural Language Processing and Quantum Machine Learning, focusing on the use of Quantum Convolutional Neural Networks (QCNNs) for sentiment analysis.The book provides a progressive introduction to the foundations of NLP, quantum computing, and Quantum Machine Learning before examining the application of QCNNs to text classification. Particular attention is given to the role of textual representation and the impact of widely used word embedding techniques, including Word2Vec, GloVe, FastText, and BERT, on QCNN-based sentiment analysis.By combining theoretical concepts with experimental investigation, this book offers a perspective on how classical language representations can be integrated with quantum learning architectures. It also discusses the current challenges and limitations of quantum NLP and highlights promising directions for future research.This book is intended for researchers, postgraduate students, and practitioners interested in NLP, quantum computing, quantum machine learning, and the emerging field of Quantum Natural Language Processing.…

Paperback. Condizione: new. Paperback. Deep and Quantum Learning for NLP explores the emerging intersection of Natural Language Processing and Quantum Machine Learning, focusing on the use of Quantum Convolutional Neural Networks (QCNNs) for sentiment analysis.The book provides a progressive introduction to the foundations of NLP, quantum computing, and Quantum Machine Learning before examining the application of QCNNs to text classification. Particular attention is given to the role of textual representation and the impact of widely used word embedding techniques, including Word2Vec, GloVe, FastText, and BERT, on QCNN-based sentiment analysis.By combining theoretical concepts with experimental investigation, this book offers a perspective on how classical language representations can be integrated with quantum learning architectures. It also discusses the current challenges and limitations of quantum NLP and highlights promising directions for future research.This book is intended for researchers, postgraduate students, and practitioners interested in NLP, quantum computing, quantum machine learning, and the emerging field of Quantum Natural Language Processing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condizione: Neu. Advanced NLP with Deep and Quantum Machine Learning | Nour El Houda Ouamane | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630478556 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Deep and Quantum Learning for NLP explores the emerging intersection of Natural Language Processing and Quantum Machine Learning, focusing on the use of Quantum Convolutional Neural Networks (QCNNs) for sentiment analysis.The book provides a progressive introduction to the foundations of NLP, quantum computing, and Quantum Machine Learning before examining the application of QCNNs to text classification. Particular attention is given to the role of textual representation and the impact of widely used word embedding techniques, including Word2Vec, GloVe, FastText, and BERT, on QCNN-based sentiment analysis.By combining theoretical concepts with experimental investigation, this book offers a perspective on how classical language representations can be integrated with quantum learning architectures. It also discusses the current challenges and limitations of quantum NLP and highlights promising directions for future research.This book is intended for researchers, postgraduate students, and practitioners interested in NLP, quantum computing, quantum machine learning, and the emerging field of Quantum Natural Language Processing. 96 pp. Englisch.…