Msd International Gmbh

Msd It Global Innovation Center S.r.o.

Shao Ying Choo

Richard Dobis

Kah Hin Chin

Yingqi Peh

Sucitro Dwijayana Sidharta

As a data science project goes into the production stage, model maintenance to maintain model quality and predictive accuracy becomes a concern. Manual model maintenance by data scientists can become a time- and labor-intensive process, especially for large scale data science projects. An early warning system addresses this by performing systematic statistical and algorithmic checks for prediction accuracy, stability, and model assumption validity. A diagnostic report is generated that helps data scientists to assess the health of the model and identify sources of error as needed. Well-performing models can be automatically deployed without further human intervention while poor performing models trigger a warning or alert to the data scientists for further investigation and may be removed from production until the performance issues are addressed.

Growing community of inventors

Singapore, Singapore

Shao Ying Choo