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Developing NLP Applications with Python
Developing NLP Applications with Python
Natural Language Processing (NLP) is transforming the way machines understand and interact with human language. Developing NLP Applications with Python is a comprehensive, practice-oriented guide designed for students, researchers, and aspiring developers who want to build real-world NLP systems using Python.
This book provides a structured approach to understanding and implementing NLP concepts, starting from basic environment setup to advanced applications such as sentiment analysis, topic modeling, chatbot development, and real-world case studies.
✔ Covers complete NLP workflow from preprocessing to deployment
✔ Includes practical examples using Python libraries like NLTK, spaCy, and scikit-learn
✔ Focuses on real-world applications such as spam detection, fake news detection, and sentiment analysis
✔ Designed for academic learning as well as hands-on development
What you will
Setting up Python for NLP developmentText preprocessing techniques and pipeline buildingFeature extraction methods like BoW, TF-IDF, and N-gramsBuilding and evaluating text classification modelsPerforming sentiment analysis on real datasetsExtracting topics using LDA and clustering techniquesImplementing Named Entity Recognition (NER) systemsMeasuring text similarity and detecting plagiarismDesigning rule-based and intelligent chatbotsDeveloping mini NLP projects and analyzing performanceWhether you are a beginner exploring NLP or a student working on academic projects, this book provides the essential knowledge and practical skills required to develop intelligent language-based applications using Python.
Natural Language Processing (NLP) is transforming the way machines understand and interact with human language. Developing NLP Applications with Python is a comprehensive, practice-oriented guide designed for students, researchers, and aspiring developers who want to build real-world NLP systems using Python.
This book provides a structured approach to understanding and implementing NLP concepts, starting from basic environment setup to advanced applications such as sentiment analysis, topic modeling, chatbot development, and real-world case studies.
✔ Covers complete NLP workflow from preprocessing to deployment
✔ Includes practical examples using Python libraries like NLTK, spaCy, and scikit-learn
✔ Focuses on real-world applications such as spam detection, fake news detection, and sentiment analysis
✔ Designed for academic learning as well as hands-on development
What you will
Setting up Python for NLP developmentText preprocessing techniques and pipeline buildingFeature extraction methods like BoW, TF-IDF, and N-gramsBuilding and evaluating text classification modelsPerforming sentiment analysis on real datasetsExtracting topics using LDA and clustering techniquesImplementing Named Entity Recognition (NER) systemsMeasuring text similarity and detecting plagiarismDesigning rule-based and intelligent chatbotsDeveloping mini NLP projects and analyzing performanceWhether you are a beginner exploring NLP or a student working on academic projects, this book provides the essential knowledge and practical skills required to develop intelligent language-based applications using Python.
115 pages, Kindle Edition
Published April 2, 2026
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