Description

As most machine learning or deep learning practitioners would agree that developing machine learning models is very different and much harder than writing and deploying software. There are certainly some of the best practices that we can leverage from the software engineering. In this session, we will improvise the Continuous Integration and Continuous Delivery (CI/CD) pipeline to apply it for a machine learning project. We will look at a demo example to demonstrate the lifecycle machine learning project using some of the offerings from Azure.

Instructor's Bio

Setu Chokshi, Director of Data Science, PropertyGuru

Setu is a senior technical leader, innovator, and specialist in machine learning and artificial intelligence. He is currently a director of DataScience at PropertyGuru, and has worked for GE and Nielsen, and has won multiple patents and awards for his work.

Recording

  • 01

    Deploying ML models into production

    • Video Recording