Our quest for robust time series forecasting at scale
Farzan Rohani · Sep 15, 2017
Date: 2017-09-15 Time: 15:30-16:30 Location: BURN 1205 Abstract: The demand for time series forecasting at Google has grown rapidly along with the company since its founding. Initially, the various business and engineering needs led to a multitude of forecasting approaches, most reliant on direct analyst support. The volume and variety of the approaches, and in some cases their inconsistency, called out for an attempt to unify, automate, and extend forecasting methods, and to distribute the results via tools that could be deployed reliably across the company.