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.
Key Takeaways
- 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
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