Azure Machine Learning is a cloud based predictive analytics service which is easy to use and give fast and reliable results using its predefined algorithms and models.

Using Machine learning in broad / high level manner needs 4 steps described as below

  1. Data collection or generation
    • Collect data from source
    • Store in Azure Storage, SQL etc
    • Refine data if needed
  2. Create Machine Learning models
    • Use Machine Learning Azure Studio
    • Easy to use drag drop interface
  3. Output data as Web Service
    • Run the model to output data as web service
  4. Use output for intelligence or insights
    • Based on output make sites or Apps intelligent
    • Create insights and make predictions

Diagram for Azure Machine Learning

azuremachinelearning
Azure Machine Learning

Published by Kislay Sinha

Hi there, I work as expert / solution architect in Microsoft 365 and Azure. I am also learning Quantum Computing and consider myself as Quantum Computing Enthusiast. In my current role I work as Enterprise Architect for On-boarding new platform / applications in organization and I also work as Solution Architect in area of Microsoft 365 and Azure. I have done multiple migrations projects, created solutions for business applications and helped organizations on-board business applications across domains and departments. My main skill sets are Microsoft 365 - SharePoint, Power Platform, Microsoft Teams Development and Migration projects Azure - Logic Apps, Modernizing and moving applications to cloud Programming skills : .Net, C#, Q#, TypeScript. sPFX

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