azuremlMary Branscombe of Tech Radar recently wrote, “We had the opportunity to interview Roger Barga, one of the architects of the Azure ML, Microsoft’s machine learning cloud service, to discuss various aspects of the system. ‘The ranking algorithm that’s in our regression module, the same one running Bing search and serving up ranked results,’ Barga told TechRadar Pro. ‘It’s our implementation on Azure but all the heuristics and know-how came from the years of experience running it. The same recommendation module we have in Azure ML is the same recommendation module that serves up in Xbox what player to play against next.’ Azure ML can look at a document, work out what it’s about and look those topics up on Bing. ‘We can say this is a company, this is a person, this is a product,’ explains Barga. ‘That’s the same way Delve will find documents and discussions and messages that you’ll want to see’.”

Branscombe continues, “For Azure ML, Microsoft mined the expertise of dozens of researchers and product teams. ‘Many of these algorithms, these guys have implemented them dozens of time. And you just can’t find that kind of expertise in a book, you can’t buy it. We are sitting on a wealth of experience and expertise.’ With existing machine learning systems, if you use the same algorithm in different systems you get different results. ‘You’re searching all possible configurations of parameters and so you have to use heuristics to find the best model with the data you have available to you. Over the years of applying these to numerous applications our colleagues in MSR and product groups figured out the optimal heuristics. We know what are the best practices, what are the heuristics, what should we do to ensure this will be robust, scalable and performant’.”

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Image: Courtesy Microsoft