●Preface
Chapter 1：Introduction
Understanding natural language processing
Understanding basic applications
Understanding advanced applications
Advantages of togetherness-N LP and Python
Environment setup for NLTK
Tips for readers
Summary
Chapter 2：Practical Understanding of a Corpus and Datase
What is a corpus?
Why do we need a corpus?
UnderStanding corpus analysis
Exercise
Understanding types of data attributes
Categorical or qualitative data attributes
Numeric or quantitative data attributes
Exploring different file formats for corpora
Resources for accessing free corpora
Preparing a dataset for NLP applications
Selecting data
Preprocessing the dataset
Formatting
Cleaning
Sampling
Transforming data
Web scraping
Summary
Chapter 3：Understanding the Structure of a Sentences
Understanding components of NLP
Natural language understanding
Natural language generation
Differences between NLU and NLG
Branches nf NLP
Defining context-free grammar
Exercise
Morphological analysis
What is morphology?
What are morphemes?
What is a stem?
What is morphological analysis?
What iS a word?
Classification of morphemes
Free morphemes
Bound morphemes
Derivational morphemes
Inflectional morphemes
What is the difference between a stem and a root?
Exercise
Lexical analysis
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