MLOps using Azure Machine Learning

Operationalising ML model release using Azure DevOps

For the longest time data science was often performed in silos, using large scale compute operating across isolated copies of production data. This process was not repeatable, explainable or scalable and often introduced business and security risk. With modern enterprises now adopting a DevOps engineering culture, no longer can machine learning development practice operate in isolation of the business or existing applications teams. This demo heavy session introduces the new Azure ML Services capabilities and how this can assist to bring the practice of data science into the age of modern DevOps.

About your speaker:
Ananth Prakash - Lead Architect - Data, AI & IoT @ Microsoft

Ananth has a successful track record in delivery of strategic projects, products and platforms in the Data & AI domain for 16+ years across North America, Australia and Asia. Some of his roles include leading product engineering groups at Oracle, Managing Consultant at IBM and Senior Technical Architect - Data & AI at Infosys. As a Lead Architect at Microsoft, Ananth helps enterprise customers architect & deploy strategic solutions on Azure to accelerate their business transformation journey