I have data regarding the energy demand of a certain consumer during the entire year but for the summer months. I would like to predict the summer time demand volumes based on those of the rest of the year. I thought of modeling using a dataset containing year long data for other consumers, but i am not so sure on how exactly to model this problem -- should I be using deep learning or rather an SVM model? I would love hearing pros and cons for both.
It is worth mentioning my data is made of half hour intervals (meaning i know the demand for every half hour of the year).