Graduate Project for Harvard's Python for Data Science (CSCI E - 29)
In this project, I pulled text data from European Parliament Proceedings in 21 languages. Using Scikit-Learn, I transformed the raw text into a numerical feature matrix, and trained a Multinomial naive bayes probability model to classify input language with greater than 99% accuracy.
Data Source: http://www.statmt.org/europarl/