Natural Language Processing with Python Updated Edition: From Basics to Advanced Projects

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TABLE OF CONTENTS
Introduction
Purpose and Scope of the Book
Who This Book Is For
How to Use This Book
Part I: Foundations of NLP
   Chapter 1: Introduction to NLP
      1.1 What is Natural Language Processing (NLP)?
      1.2 Significance and Applications of NLP
      1.3 Overview of Python for NLP
      Practical Exercises
      Chapter 1 Summary
   Chapter 2: Basic Text Processing
      2.1 Understanding Text Data
      2.2 Text Cleaning: Stop Word Removal, Stemming, Lemmatization
      2.3 Regular Expressions
      2.4 Tokenization
      Practical Exercises
      Chapter 2 Summary
   Chapter 3: Feature Engineering for NLP
      3.1 Bag of Words
      3.2 TF-IDF
      3.3 Word Embeddings (Word2Vec, GloVe)
      3.4 Introduction to BERT Embeddings
      Practical Exercises
      Chapter Summary
   Quiz Part I: Foundations of NLP
      Chapter 1: Introduction to NLP
      Chapter 2: Basic Text Processing
      Chapter 3: Feature Engineering for NLP
      Practical Applications
      Code Implementation
      Conceptual Understanding
      Advanced Understanding
      Answers
      Chapter 3: Feature Engineering for NLP
Part II: Advanced Text Processing and Modeling
   Chapter 4: Language Modeling
      4.1 N-grams
      4.2 Hidden Markov Models
      4.3 Recurrent Neural Networks (RNNs)
      4.4 Long Short-Term Memory Networks (LSTMs)
      Practical Exercises
      Chapter Summary
   Chapter 5: Syntax and Parsing
      5.1 Parts of Speech (POS) Tagging
      5.2 Named Entity Recognition (NER)
      5.3 Dependency Parsing
      Practical Exercises
      Chapter Summary
   Chapter 6: Sentiment Analysis
      6.1 Rule-Based Approaches
      6.2 Machine Learning Approaches
      6.3 Deep Learning Approaches
      Practical Exercises
      Chapter Summary
   Quiz Part II: Advanced Text Processing and Modeling
      Chapter 4: Language Modeling
      Chapter 5: Syntax and Parsing
      Chapter 6: Sentiment Analysis
      Answers
Part III: Topic Modeling and Text Summarization
   Chapter 7: Topic Modeling
      7.1 Latent Semantic Analysis (LSA)
      7.2 Latent Dirichlet Allocation (LDA)
      7.3 Hierarchical Dirichlet Process (HDP)
      Practical Exercises
      Chapter Summary
   Chapter 8: Text Summarization
      8.1 Extractive Summarization
      8.2 Abstractive Summarization
      Practical Exercises
      Chapter Summary
   Quiz Part III: Topic Modeling and Text Summarization
      Chapter 7: Topic Modeling
      Chapter 8: Text Summarization
      Answers
Part IV: Applications and Advanced Techniques
   Chapter 9: Machine Translation
      9.1 Sequence to Sequence Models
      9.2 Attention Mechanisms
      9.3 Transformer Models
      Practical Exercises
      Chapter Summary
   Chapter 10: Introduction to Chatbots
      10.1 What is a Chatbot?
      10.2 Applications of Chatbots
      10.3 Types of Chatbots: Rule-Based, Self-Learning, and Hybrid
      Practical Exercises
      Chapter Summary
   Chapter 11: Chatbot Project: Personal Assistant Chatbot
      11.1 Project Introduction and Design
      11.2 Data Collection and Preprocessing
      11.3 Building and Training the Chatbot
      11.4 Evaluating and Deploying the Chatbot
      11.5 Improving and Maintaining the Chatbot
      Chapter Summary
   Chapter 12: Project: News Aggregator
      12.1 Project Introduction and Design
      12.2 Data Collection and Preprocessing
      12.3 Implementing Text Summarization and Topic Modeling
      12.4 Building the User Interface
      12.5 Evaluating and Deploying the Aggregator
      Chapter Summary
   Chapter 13: Project: Sentiment Analysis Dashboard
      13.1 Project Introduction and Design
      13.2 Data Collection and Preprocessing
      13.3 Building and Training Sentiment Analysis Models
      13.4 Developing the Dashboard Interface
      13.5 Evaluating and Deploying the Dashboard
      Chapter Summary
   Quiz Part IV: Applications and Advanced Techniques
      Chapter 9: Machine Translation
      Chapter 10: Introduction to Chatbots
      Chapter 11: Chatbot Project: Personal Assistant Chatbot
      Chapter 12: Project: News Aggregator
      Chapter 13: Project: Sentiment Analysis Dashboard
      Answer Key
Conclusion
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