Comparative Analysis of Statistical and Deep Learning Models for Hourly Traffic Volume Forecasting

This time series project uses weather and holiday features to predict hourly traffic volume between Minneapolis and St Paul, MN with data from October 2, 2012 till September 30, 2018. Several time series techniques were used to find an appropriate prediction model. The project progresses from data preprocessing, time series decomposition, multiple model development and evaluation using standard metrics.