Natural Language Processing in the Real World: Text Processing, Analytics, and Classification (Chapman & Hall/CRC Data Science Series)

Description

Natural Language Processing in the Real World: Text Processing, Analytics, and Classification provides a hands-on introduction to applying natural language processing (NLP) techniques to real-world data challenges.

Part of the Chapman & Hall/CRC Data Science Series, this book focuses on practical methods for working with unstructured text data. Readers learn how to preprocess text, extract meaningful features, and apply machine learning models for text analytics and classification tasks.

The book covers essential NLP topics such as tokenization, normalization, vectorization, topic modeling, sentiment analysis, and document classification. Emphasis is placed on real-world use cases, helping readers understand how NLP techniques are applied in industry settings such as information retrieval, customer feedback analysis, and content categorization.

Written for data scientists, analysts, and developers, this book bridges theory and practice by combining clear explanations with applied examples. It serves as a valuable resource for anyone looking to build scalable and effective NLP solutions using modern data science techniques.

Key highlights include:
Practical natural language processing for real-world applications
Text processing, analytics, and classification techniques
Machine learning approaches for NLP tasks
Ideal for data scientists, analysts, and NLP practitioners