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Can Microsoft's Azure bring machine learning to the masses?

Jonathan Hassell | July 21, 2015
While the very phrase 'machine learning' may conjure up fantastic images of evil robot overlords and other science fiction references, the technology as been around for some time. Here’s how Microsoft aims to make it as available and easy to use as any other software program.

Once the data scientist is ready to publish, that's when tested models become available to developers via the API service. The business users can access results, from anywhere, on any device. And any model updates simply refresh the model in production with no new development work needed. It is essentially machine learning as a service (MLaaS?).

Azure Machine Learning is already in use by many companies who are using the service in the following ways:

  • telemetry data analysis
  • buyer propensity models
  • social network analysis
  • predictive maintenance
  • Web app optimization
  • churn analysis
  • natural resource exploration
  • weather forecasting
  • predictive healthcare outcomes
  • financial fraud detection
  • life sciences research
  • targeted advertising
  • network intrusion detection
  • smart meter monitoring

The last word on machine learning
Microsoft's goal with Azure Machine Learning is to make it easy to get started with the data you already have and the staff you already employ just start an Azure subscription, set up a workspace and start playing in the ML Studio. Microsoft provides ample additional technical documentation and access to a 30-day free trial. You can also browse the ML Studio gallery to find five-minute educational tutorials on how to get sample data, run experiments, and more.


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