Text analytics with python : a practical real-world approach to gaining actionable insights from your data /
by Dipanjan Sarkar.
- 2nd ed.
- Karnataka : Apress, 2019.
- xxiv, 674 p. ; ill. ; 24 cm
Includes bibliographical references and index.
Introduction -- Natural language basics -- Python refresher -- Processing and understanding text -- Text classification -- Text summarization -- Text similarity and clustering -- Semantic and sentiment analysis.
The second edition of this book focuses on Natural Language Processing (NLP) in Python and how to set up a robust environment for text analytics. It introduces state-of-the-art frameworks in NLP, along with Machine Learning and Deep Learning, to solve real-world case studies. The book includes a dedicated chapter on Python for NLP, feature engineering representation methods, and techniques for parsing and processing text data. It also covers text classification, text summarization, text similarity techniques, sentiment analysis, machine learning and deep learning models, semantic analysis, and deep transfer learning. The book will be updated to the latest Python 3.x release, showcasing diverse NLP applications such as classification, clustering, similarity recommenders, topic models, sentiment and semantic analysis.
9781484243534
Python (Computer program language) Natural language processing (Computer science) Natural language processing (Computer science) Python (Computer program language) Text Mining Artificial intelligence.