Multivariate time-series forecasting is a non-trivial task when it comes to complex seasonality. Forecasting: Principles and Practice by R.J. Hyndman and G. Athanasopoulo, gives several powerful examples if you’re using R and dealing with seasonality using Fourier terms for each seasonal period (kinda like I did in this post). In this post I’ll be using’s Keras RNN’s module for LSTM in python and forecasting the next 24 hours of call volume, per hour, into the future using the past 24 hours of my EMS data along with hourly weather data from Central Park via the NOAA.