Intro to WordNet and NLTK (zip, jupyter nbviewer, GitHub
Topic Modeling with MALLET (zip, jupyter nbviewer, GitHub repo)
Intro to the Forward Algorithm (zip, jupyter nbviewer)
Intro to the Backward Algorithm (zip, jupyter nbviewer)
I was porting some Finite State algorithms to Python
3 for some
more or less functional FST-lib for Weighted Finite State Transducers
in native Python, and code generation to C for example. I will place the
code on GitHub: Project PyFST
Here is some of the material from my Python classes and developments.
Some of it is from the late 90s, so it might be outdated, and not
really working in Python 3.x.
Some of the Python examples and tutorials (slides and instruction
handouts) for corpus, data and language processing are adapted to Python 3.
lightweight module with functions for creating and using n-gram models
for statistical analyses, various statistical functions, chi2 test,
vector space conversion of n-gram models, entropy and information
theoretic measures etc. There are examples for document classification,
measures of text or model similarity and various other useful functions.