Final project for Deep Learning for Natural Language Processing.

We apply various feedforward neural networks to the task of classifying a Google NGram to a twenty year period within the last 200 years or to modeling the distribution through time of these ngrams. We also try learning combined "phrase vectors" from the word vectors for each word in the ngram using an LSTM-RNN.