Time series prediction of web traffic data
In this thesis we predict web traffic intensity levels for 7 customers of a cybersecurity company. The models we predict with are a SARIMA model and a Temporal convolutional network. The quality of the predictions vary a lot between the different customers. The predictions improve when performed on data that is logged, demeaned and differenced.