Aman Kedia - Hands-On Python Natural Language Processing: Explore tools and techniques to analyze and process text with a view to building real-world NLP applications

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Aman Kedia is a data enthusiast and lifelong learner. He is an avid believer in Artificial Intelligence (AI) and the algorithms supporting it. He has worked on state-of-the-art problems in Natural Language Processing (NLP), encompassing resume matching and digital assistants, among others. He has worked at Oracle and SAP, trying to solve problems leveraging advancements in AI. He has four published research papers in the domain of AI.

Mayank Rasu has more than 12 years of global experience as a data scientist and quantitative analyst in the investment banking industry. He has worked at the intersection of finance and technology and has developed and deployed AI-based applications within the finance domain. His experience includes building sentiment analyzers, robotics, and deep learning-based document review, among many others areas.

Dr. Deepti Chopra has a Ph.D. in computer science and engineering from Banasthali Vidyapith. She has taught for 4 years as an assistant professor in the Department of Computer Science at Banasthali Vidyapith. Currently, she is working as an assistant professor (IT) at Lal Bahadur Shastri Institute of Management. Her areas of interest include AI, NLP, and computational linguistics. She has written several research papers for various international conferences and journals. Also, she is the author of three books and one MOOC.

Dr. Dhirendra Pratap Singh is a passionate NLP research scholar who strongly believes deep learning techniques can resolve any NLP research problem. His Ph.D. is focused on semantics and information extraction and retrieval using deep learning techniques. He has a good demonstrating background in his academic and industrial research. He has been invited by many prestigious universities for academic talks, including IIT Bombay, Guwahati, JNU, SRM Engineering University, University of Tokyo, and so on. He has publications at top NLP conferences including NAACL, GWC, ICON, LREC, and LSI. Currently, he is associated with two NLP-AI companies (Lionbridge Technologies and Appen) for opening up new ideas for research projects in computational linguistics.

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This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP-based use cases such as language translation, sentiment analysis, chatbots, and many more. The book also goes into the details of the application of machine learning and deep learning in improving the efficiency of NLP applications and introduces readers to the recent developments in this field. Every module covers real-world examples that can be replicated and built upon.

This book is for anyone interested in NLP who is seeking to learn about its theoretical and practical aspects alike. The book starts from the basics and gradually progresses to more advanced concepts, making it suitable for an audience with varying levels of prior NLP proficiency, and for those who want to develop a thorough understanding of NLP methodologies to build linguistic applications. However, a working knowledge of the Python programming language and high-school-level mathematics is expected.

, Understanding the Basics of NLP