This is the first project I've decided to do in Artificial Intelligence. I've started getting quite a passion for the subject and its potential applications. This uses natural language processing (NLP) for binary classification from a multi-layer perceptron (MLP) i.e. standard neural network. It attempts to predict the EUR/USD appreciation/depreciation from the Fed's Monetary Policy Report release date up until the next report release to Congress.
Since this is my first project, the model is quite elementary. I was able to get an 80% level of accuracy on my cross validation set, but it doesn't provide anything statistically significant on the test set (It doesn't provide a higher level of accuracy than 50%). Never-the-less, by using more advanced features in Keras and Hyperas/Hyperopt, I've already gotten a statistically significant result on my test set with another model I'm currently working on. I will be publishing that soon.
If there are issues with accessing my Gihub repo below, I have a zipped file with my code, model, and datasets here: Repo Copy
Please see my Github for code and datasets related to this project.