The general concept behind this project is a hashtag generator. I used data taken from twitter to train a Recurrent Neural Network using the OpenNMT-py library. The idea is that if you feed the Neural Network a tweet or sentence, it can suggest appropriate hashtags. I chose the Recurrent Neural Network Sequence to Sequence model because it had the ability to generate novel hashtags, as opposed to another strategy that would have been limited to a set of hashtags/classes. Ultimately, I decided to do this project to explore a novel and potentially entertaining use of a sequence to sequence generator. In the process, I learned about several things including how to consume and clean data from twitter, the training process of Neural Networks, and how to use the OpenNMT-py library.
The model took just over 36 hours to train on a training set of about 2900 examples. I definitely have a greater appreciation for how much computing power is required to