Apache® Spark™ News

The Delta Between ML Today and Efficient ML Tomorrow

If you are working as a data scientist, you might have your full modelling process sorted and potentially have even deployed a machine learning model into production using MLflow. You might have experimented using MLflow tracking and promoted models using the MLflow Model Registry. You are probably quite happy with the reproducibility this provides, as you are able to track things like code version, cluster set-up and also data location.