Global Datathon Finals Online Streaming

Datathon Kaufland Solution – Team Total Kaputt! – Why da faQ the machine broke down?

Posted milena-piryankova, stephen, nike, bogomil-filipov, vasilmarchev, martinmarinov, sergeyvi4ev, michael-opitsch, penchodobrev, sist Mentors: junior, pepe5 CommentsPosted in Prediction systems

What we tried to do to solve the Kaufland case for the Global Datathon 2018. This article just contains our exploratory data analysis in the form of many plots and some explanations. There isn’t any modeling stage described here.

Datathon Kaufland Solution – LSTM and EDM Models for Predictive Maintenance

Posted kenghooi, narjes, avkmal, finlayyee, michael-opitsch, penchodobrev, sist35 CommentsPosted in Datathons Solutions

In this paper we propose the use of a combination of LSTM and EDM models to address the issue of anomaly classification and prediction in time series data. Working with sensor data for automated storage and retrieval systems for a German hypermarket chain, we show that predictors based on variance and median methods show sufficient promise in the handling of anomalies.