Mastering Natural Language Processing with Python

More Information
Learn
  • Implement string matching algorithms and normalization techniques
  • Implement statistical language modeling techniques
  • Get an insight into developing a stemmer, lemmatizer, morphological analyzer, and morphological generator
  • Develop a search engine and implement POS tagging concepts and statistical modeling concepts involving the n gram approach
  • Familiarize yourself with concepts such as the Treebank construct, CFG construction, the CYK Chart Parsing algorithm, and the Earley Chart Parsing algorithm
  • Develop an NER-based system and understand and apply the concepts of sentiment analysis
  • Understand and implement the concepts of Information Retrieval and text summarization
  • Develop a Discourse Analysis System and Anaphora Resolution based system
About

Natural Language Processing is one of the fields of computational linguistics and artificial intelligence that is concerned with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning.

This book will give you expertise on how to employ various NLP tasks in Python, giving you an insight into the best practices when designing and building NLP-based applications using Python. It will help you become an expert in no time and assist you in creating your own NLP projects using NLTK.

You will sequentially be guided through applying machine learning tools to develop various models. We’ll give you clarity on how to create training data and how to implement major NLP applications such as Named Entity Recognition, Question Answering System, Discourse Analysis, Transliteration, Word Sense disambiguation, Information Retrieval, Sentiment Analysis, Text Summarization, and Anaphora Resolution.

Features
  • Learn to implement various NLP tasks in Python
  • Gain insights into the current and budding research topics of NLP
  • This is a comprehensive step-by-step guide to help students and researchers create their own projects based on real-life applications
Page Count 238
Course Length 7 hours 8 minutes
ISBN 9781783989041
Date Of Publication 9 Jun 2016

Authors

Deepti Chopra

Deepti Chopra is an Assistant Professor at Banasthali University. Her primary area of research is computational linguistics, Natural Language Processing, and artificial intelligence. She is also involved in the development of MT engines for English to Indian languages. She has several publications in various journals and conferences and also serves on the program committees of several conferences and journals.

Nisheeth Joshi

Nisheeth Joshi is an associate professor and a researcher at Banasthali University. He has also done a PhD in Natural Language Processing. He is an expert with the TDIL Program, Department of IT, Government of India, the premier organization overseeing language technology funding and research in India. He has several publications to his name in various journals and conferences, and also serves on the program committees and editorial boards of several conferences and journals.

Iti Mathur

Iti Mathur is an Assistant Professor at Banasthali University. Her areas of interest are computational semantics and ontological engineering. Besides this, she is also involved in the development of MT engines for English to Indian languages. She is one of the experts empaneled with TDIL program, Department of Electronics and Information Technology (DeitY), Govt. of India, a premier organization that oversees Language Technology Funding and Research in India. She has several publications in various journals and conferences and also serves on the program committees and editorial boards of several conferences and journals.