Various jupyter nbs that preprocess different text inputs, vectorize and prepare the text for different machine learning models. And various supervised amnd unsupervised models to execute on the data.

** These scripts borrow heavily from Applied Text Analysis with Python By Benjamin Bengfort, Rebecca Bilbro and Tony Ojeda **

Takes both text and PDF docs previously dowloaded and creates a corpous reader, and leverages spacy to id sentences, tokenize text, remove stop words and creates lists of lists of preprocessed text. Finally, it pickles the files so they can be read from disk.

Additionally, data is then vectorized in various ways in preparation for use in the different ML models.

Takes preprocessed data and creates a pipeline of the variouos class obects, selects various models and trains and fits the models, generating various performance metrics.