As a new investor in stocks, I didn't want to lose all my money right away ;). Hence, I wanted to create something that would strengthen my decisions for which stocks I should invest in. Thus, using Keras and various other python libraries such as, Numpy, Matplotlib, and Pandas, I was able to create a RNN (Recurrent Neural Network) stock predicator for the Google stocks. This was done by analyzing previous trends, based on the stock's opening price. The training data set starts from March 3rd, 2012 to December 30th, 2016. My test data starts from January 3rd, 2017 to January 31st, 2017. The output will be in the form of a graph.
Future Improvements: This model is not as accurate as I want it to be, which is why it still needs work, however, it is able to give rough ideas about what is going to come in the future.