Companies and Governments across the globe are pouring billions of dollars into AI. The projects are getting ever more interesting and complex, and it is therefore natural to conclude that these projects need management. In this course, Managing Microsoft Azure AI Solutions, I assert that an AI project is like any other software project, and the need to manage it with good software practices is more, not less, important. With demos, you’ll learn how you can use concepts such as Azure CLI, ML SDK, and ML Ops to fully automate your end to end process. You’ll also explore how you can set up an Azure DevOps pipeline to go from experiment to a service. But the fun doesn’t end there; you’ll then discover how to deploy your model as an AKS cluster and enable data monitoring and collection in production, so you can use that data in numerous ways to analyze it or feed it back into your model for subsequent improvement. By the end of this course, you’ll have an in-depth understanding of how to manage your AI projects like a proper software project. Concepts such as ML Ops and Pipelines will be second nature to you, and you’ll be a pro at collecting and monitoring your production AI solutions.
Author Name: Sahil Malik
Author Description:
Sahil Malik, the founder and principal of Winsmarts.com, has been a Microsoft MVP and INETA Speaker for the past 8 years, author and reviewer of many books and numerous articles in both the .NET and SharePoint space, consultant and trainer who delivers training and talks at conferences internationally. Sahil has trained for the best names in the Microsoft technology space, and has architected and delivered SharePoint based solutions for extremely high profile clients. Sahil has been deeply invol… more

Table of Contents

• Course Overview
  1min
• Managing Models in Azure Machine Learning Service
  11mins
• Registering Your Model
  41mins
• Registering and Deploying Your Image
  15mins
• Monitoring and Improving Data and Models
  26mins
• Wrapping Up
  3mins