MLOps at Walgreens Boots Alliance With Databricks Lakehouse Platform - Tech news 03

On this weblog, we introduce the rising significance of MLOps and the MLOps accelerator co-developed by Walgreens Boots Alliance (WBA) and Databricks. The MLOps accelerator is designed to standardize ML practices, scale back the time to productionize ML mannequin, increase collaboration between knowledge scientists and ML engineers, and generate enterprise values and return of funding on AI. All through this submit, we clarify the purposes of MLOps on the Databricks Lakehouse Platform, how WBA automates and standarizes MLOps, and how one can replicate their success. MLOps, the composition of DevOps DataOps ModelOps, is a set of processes and automation to assist organizations handle code, knowledge, and fashions. However placing MLOps into observe comes with its challenges. In machine studying (ML) methods, fashions, code, and knowledge all evolve over time, which might create friction round refresh schedules and ML pipelines; in the meantime, mannequin efficiency could degrade over time as knowledge drifts requiring the mannequin to be retrained.