NLP

I have put together my notes for the undergraduate NLP class I teach in book form. 

Exploring NLP with Python is available on Amazon

Most chapters have companion videos on my YouTube channel.

Code examples are available on GitHub

Part 1: Foundations
  • Chapter 1: A Brief and Biased Overview of NLP 
  • Chapter 2: Python Basics 
  • Chapter 3: Intro to NLTK
  • Chapter 4: Linguistics 101

Part 2: Words
  • Chapter 5: Words and Counting
  • Chapter 6: POS Tagging
  • Chapter 7: Relationships between Words
  • Chapter 8: N-gram Models

Part 3: Sentences
  • Chapter 9: CFG Grammar
  • Chapter 10: Syntax and Parsing
  • Chapter 11: Annotated Parses

Part 4: Documents
  • Chapter 12: Finding or Building Corpora
  • Chapter 13: Information Extraction
  • Chapter 14: Vector-Space Models
  • Chapter 15: Topic Modeling
  • Chapter 16: Semantics

Part 5: Machine Learning
  • Chapter 17: Machine Learning
  • Chapter 18: NumPy, pandas, Scikit-Learn, Seaborn
  • Chapter 19: Converting Text to Numeric Data
  • Chapter 20: Naive Bayes
  • Chapter 21: Logistic Regression
  • Chapter 22: Neural Networks

Part 6: Deep Learning
  • Chapter 23: Deep Learning 
  • Chapter 24: Deep Learning Variations
  • Chapter 25: Embeddings
  • Chapter 26: Encoders and Decoders

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