HA10.py alters email texts such that they will pass a given spam filter.
HA4.py automatically detects the language of given texts by comparing character frequencies
HA5.py calculates the similarity of word using WordNet and compares the rank to a human assessment
HA6.py implements a T9-like SMS word completion algorithm
HA7.py finds Homonyms and prints example usages for each possible meaning
HA8.py uses a perceptron tagger to annotate words in a corpus with POS-tags
HA9.py a bayesian classifier to annotate words with POS-tags and ranks the features by informativeness
HW3.py finds the most improbable phrases in a text by using log-likelyhood