In this project, we use a recurrent neural network to predict the trajectory paths of hurricanes. We use the Hurricane Database dataset from Unisys Weather. Here we preprocess the data, train a recurrent neural network on some of the samples, and compare our predictions against the real hurricanes. So far, we're using only the years 2000 to 2009 and is saved on our repo as '2000-2009-data.csv'.
The model was implemented using Python 3.6. The code was written and run in a Jupyter notebook. For local installation, make sure you have pip installed and run:
$ pip install notebook
Then to run, you would launch the notebook with:
$ jupyter notebook
The project successfully trains a model, however graphing the trajectories (latitude and longitude points) needs work. That graphing is under construction.