We are being asked more and more to work with various aspects of data, regardless of our core skill set. This is particularly the case when productionising Machine Learning Models.

In this session we will talk about various Azure technologies we can use in our day jobs to achieve this, including ML Studio, Databricks & AKS.

We will look at the various components needed and different architectures that can be implemented, including how to manage Feature Stores and monitoring Model Life Cycles.

When working with data it is vital that different Data Professionals, Software Developers/Engineers & others in tech work in harmony together for successful outcomes. Consequently we will also cover how we can try to best achieve this, and how this has been done in the real world.