By Fernando Pereira University of Pennsylvania
Machine Learning in Natural Language Processing by Fernando Pereira explores the intersection of machine learning techniques and natural language processing (NLP). The book provides a foundational understanding of how algorithms such as decision trees, maximum entropy models, and neural networks are applied to NLP tasks like parsing, tagging, and information extraction. With a focus on real-world applications and theoretical insights, it is an essential read for students and professionals aiming to build intelligent language-based systems.
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