by Graham Neubig (neubig at is dot naist.jp)
This is a tutorial to learn the basics of natural language processing and machine learning through programming exercises using Python. The tutorial files are in the "download" directory, so please open up this directory and view the PDF there.
The tutorial covers the following material:
- Tutorial 0: Programming Basics
- Tutorial 1: Unigram Language Models
- Tutorial 2: Bigram Language Models
- Tutorial 3: The Perceptron Algorithm
- Tutorial 4: Word Segmentation
- Tutorial 5: Part-of-Speech Tagging with Hidden Markov Models
- Tutorial 6: Kana-Kanji Conversion for Japanese Input
- Tutorial 7: Topic Models
- Tutorial 8: Phrase Structure Parsing
- Tutorial 9: Advanced Discriminative Training
- Tutorial 10: Neural Networks
- Tutorial 11: Structured Perceptron
- Tutorial 12: Dependency Parsing
- Tutorial 13: Search Algorithms