Customer manages a fleet of machines transmitting daily aggregated telemetry data. He engaged with the EMEA prototype team to better understand machine event rates to improve his machine maintenance and provisioning.

The customer provides you with a sample dataset with machine events statistics. The dataset is partitioned by day and contains the machine serial number, a boolean that indicates if the machine had event (1=event) that specific day or not (=0) and (9) features that characterize the machine. You are tasked with building a model using machine learning to predict the probability of a machine event.