Munaf A Qazi
Munaf is a Machine Learning Engineer at Munich Re standardizing MLOPs processes and the model retraining infrastructure for the North American Integrated Analytics team. Previously, Munaf was a Research Scientist at NYU passionate about data provenance and Auto ML. He also has multiple years of experience as a data scientist analyzing financial, consumer and digital data.
In his free time he tinkers with raspberry pis building fun gadgets in his miniworkshop.
Sessions
An important aspect of having a healthy Machine Learning Operations (MLOps) pipeline in a production setting is the ability to retrain models as required. This might be as a response to changes in the data distribution, performance degradation or at well-defined time posts due to, for example, regulatory requirements.