Natural Language Processing

Description

Natural Language Processing is a comprehensive guide designed for undergraduate students, academicians, industry professionals, and researchers in computer science, information technology, and artificial intelligence. It provides a thorough understanding of NLP techniques and insights into the rapidly evolving landscape of language technology.

The book begins by laying the groundwork in Machine Learning (ML) and Deep Learning (DL), introducing key NLP applications and obstacles such as Word Sense Disambiguation. Readers will learn to configure crucial software like NLTK, Anaconda, and Jupyter Notebooks, preparing them for practical exercises. Advanced NLP concepts are covered, including Regular Expressions, TF-IDF, Word2Vec, and Named Entity Recognition (NER), alongside concrete implementations of Sentiment Analysis and Topic Modeling. The text thoroughly examines RNNs, LSTMs, and state-of the-art Transformer-based models like BERT and GPT-3, providing step-by-step guidance on finetuning these models for specific tasks. Topics like ethical implications in NLP, particularly AI model bias, emphasizing responsible AI deployment have been covered in detail. The book concludes with real-world case studies and a comprehensive section on interview questions, equipping readers with the knowledge and skills to thrive in this field.

About the authors:

Prof. Sini Raj Pulari, with 17 years of experience in reputed Indian universities and industry, currently serves at Bahrain Polytechnic in the Kingdom of Bahrain. She specializes in Computer Science Engineering, contributing to teaching, research, and professional activities. Her research interests focus on Natural Language Processing, Recommender Systems, Information Retrieval, Deep Learning, and Machine Learning. Prof. Sini has authored over 30 publications, including the books Deep Learning: A Comprehensive Guide and Machine Learning using Intel oneAPI (CRC Press). She is currently pursuing her Ph.D. in Natural Language Processing at Vignan’s Foundation for Science, Technology and Research (Deemed to be University). Prof. Sini has guided more than 50 UG and PG students on innovative product-based projects an algorithmic ideas. Additionally, She was actively involved in a funded project on the Early Warning and Monitoring System for Elephants. She has delivered 50+ invited lectures on technological trends and participated in key workshops, including “AI for ALL” and the MENA Hackathon. Prof. Sini also led a 21-day AICTE TEQIP Deep Learning session, partnered with Tamkeen and AWS. She has organized and participated in various national and international events, holding multiple certifications, including Apple Certified Trainer, SCJP, Oracle Certified Associate, and Intel Certified Instructor.

Dr Umadevi Maramreddy is an Associate Professor in the Department of Computer Science and Engineering at Vignan’s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh. She earned her PhD in Computer Science from the University of Hyderabad in 2011, specializing in Document Forensics. With 19 years of experience, including 4 years in research and 15 years in teaching, Dr Umadevi has previously served as Head of the CSE Department in various engineering colleges. Her research interests include Printed Document Forensics, Image Processing, Soft Computing, Natural Language Processing, and Machine Learning. Dr Umadevi is also a reviewer and technical committee member for multiple international conferences and is actively involved in professional bodies like CSI and IAENG.

Dr Umadevi has made significant contributions to both academia and research, playing an instrumental role in advancing her fields of interest. She has also been recognized in academic circles through platforms like Google Scholar, ORCID, and Scopus. Dr Umadevi remains committed to expanding her expertise and contributing to cutting-edge research in computer science and engineering.

Dr Shriram K. Vasudevan has over 18 years of combined experience in industry and academia. He holds a Doctorate in Embedded Systems and has authored or co-authored 46 books for renowned publishers such as Oxford University Press, Taylor and Francis, and Wiley. With 14 patents granted to his name, Dr Shriram is a prolific innovator and researcher, having published over 150 research articles.  An avid hackathon enthusiast, Dr Shriram has received awards from prestigious institutions and organizations including Harvard University, AICTE, CII, Google, TDRA Dubai, the Government of Saudi Arabia, and the Government of India. Before his current role, he was associated with L&T Technology Services. Dr Shriram runs a popular YouTube channel with more than 48k subscribers, where he shares knowledge on a wide range of topics. As a public speaker, he has been recognized as an Intel oneAPI Certified Instructor, Google Cloud Ambassador, Streamlit Education Ambassador, AWS Ambassador, ACM Distinguished Speaker,NASSCOM External Mentor and NASSCOM Prime Ambassador. He is also a Fellow of IEI and IETE, a Senior Member of IEEE, and has been acknowledged by LinkedIn as a TOP AI VOICE. Additionally, Dr Shriram is a TEDx speaker, showcasing his expertise and influence in the field of AI and technology.

Table of contents

Introduction to Machine Learning and Deep Learning

Natural Language Processing – An Introduction

The Installations for NLP

Regular Expressions – Must Know Pre-requisite for NLP

Introduction of Important Terminologies in NLP and Text Pre-processing

Semantic Inference in NLP 

Named Entity Recognition – A Detailed Walkthrough

Word Embeddings in NLP

Text classification in NLP – A Quick Walk Through

The RNNs, LSTMs, and GRUs –A Walk Through

Transformer Based Models in NLP

Text Summarization Techniques in NLP

Real-time case studies with Natural Language Processing

Ethical Considerations in NLP and Bias Mitigation

Prompt Engineering – A Quick Review