Microsoft is demonstrating the machine learning capabilities of the Azure cloud through a Web site that guesses the ages of people in uploaded photos.
Microsoft’s newly released Face detection API’s powers a webpage called http://how-old.net. This page lets users upload a picture and have the API predict the age and gender of any faces recognized in that picture.
According to Joseph Sirosh, Microsoft corporate vice president in the company's cloud and enterprise group, the key system behind the face detection solution first extracts the gender and age of the people in the submitted pictures. It then obtains real time insights on the data extracted and creates real time dashboards to view the above results.
Data was collected and analyzed using a set of Microsoft Azure streaming services and specifically the Azure Event Hubs, a highly scalable publish-subscribe ingestor that can intake millions of events per second. Microsoft used the Event Hubs API to stream the JSON document from the web page when the user uploads a picture. Note that the picture is not saved, just the metadata extracted in the JSON file gets streamed to Event Hubs.
The next step needed was a stream processing service to aggregate and process the information from thousands of users uploading pictures in real time. For this Microsoft used Azure Stream Analytics (ASA), a fully managed low latency high throughput stream processing solution. ASA lets you write your stream processing logic in a simple SQL -like language.
PowerBI was then used to display the results in a real time dashboard.
PowerBI lets you create a variety of visualizations including maps, line charts, tree view charts and more.
Machine learning is a type of data analysis that allows computers to draw inferences from large sets of data, by building predictive models through repeated sampling of data.
Microsoft launched its commercial machine learning service in February.