The session gives an overview on some typical fields to use machine learning in production. Based on a case study (stud welding) we show typical methods like classification and root cause analysis. Further first approaches towards explainability are introduced. Finally we present open challenges regarding ML in production.
- From data perspective various topics(problems) in production are similar
- Necessary basics to be setup for scaling
- First steps towards explainability of models
- Further challenges regarding data and Ml regarding production data