Advanced NLP with Deep and Quantum Machine Learning

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.