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Full Description
This book provides a thorough and comprehensive introduction to natural language processing (NLP), a critical field at the intersection of artificial intelligence and computational linguistics. It explores key techniques such as sentiment analysis, which enables the detection of emotional tone in text, machine translation, facilitating the conversion of text between languages, and named entity recognition (NER), which identifies and classifies entities like names, dates, and locations within text data.
The book delves into deep learning advancements, particularly the use of neural networks such as transformers and recurrent models, which have revolutionized NLP applications. Readers will gain insights into how these models drive innovations in areas such as text classification, language generation, and speech recognition.
In addition to technical concepts, the book also addresses the ethical considerations surrounding NLP, emphasizing the responsible use of AI technologies to mitigate issues like bias, misinformation, and privacy concerns. Practical case studies and real-world examples are included to illustrate how NLP is applied in various sectors, including healthcare, finance, and customer service.
This book is an invaluable resource for students, researchers, and industry professionals seeking to understand the foundational concepts, cutting-edge advancements, and broader implications of NLP, equipping them with the knowledge to innovate and apply these technologies effectively in their respective fields.
Contents
1. Introduction 2. Parsing and Syntax 3. Smoothed Estimation and Language Modelling 4. Semantic Analysis and Discourse Processing 5. Natural Language Generation and Machine Translation 6. Information Retrieval and Lexical Resurces 7. Unsupervised Methods in NLP 8. Summary 9. Conclusion
