The ML Lifecycle management process is quickly becoming the bottleneck for a lot of ML projects. With MLflow’s newest release, and its enhanced integration with Azure Machine Learning, this process is now showing the right promise and capabilities on Azure. In this talk, we intend to take a tour of the integration details and how MLOps is now becoming a strength of the platform. We’ll talk about versioning, maintaining run history, production pipeline automation, deployment to cloud and edge, and CI/CD pipelines with MLOps as the backdrop.
Be prepared for an interactive conversation as we intend to seek a lot of feedback on the integration and capabilities being lit up.
Nishant leads technical product management for Microsoft's ML portfolio. He has a degree in Computer Science specializing on Data Structures and Algorithms. With more than 12 years of experience in the Big Data Analytics and AI space, he brings keen observations from key customer implementation on Azure.