Microsoft Researcher Talks About The History Of Machine Learning At Microsoft

 John Platt, a Distinguished Scientist at Microsoft Research today blogged about the history of machine learning at Microsoft. Machine Learning has become a buzz word these days, thanks to consumer facing features such as Cortana, Google Now, etc. Microsoft is using the concepts of machine learning for over 20 years starting in 1992. It is being used in content-based spam detector, speech recognition, predictive analytics to the Commerce Server product, Data mining product in SQL Server, and more. More recently, Microsoft announced Microsoft Azure ML which will allow users to create models that can be deployed to the cloud, rather than being restricted to one particular data management platform (such as SQL).

The story of ML at Microsoft started in 1992. We started working with Bayesian Networks, language modeling, and speech recognition. By 1993, Eric Horvitz, David Heckerman, and Jack Breese started the Decision Theory Group in Research and XD Huang started the Speech Recognition Group. In the 90s, we found that many problems, such as text categorization and email prioritization, were solvable through a combination of linear classification and Bayes networks. That work produced the first content-based spam detector and a number of other prototypes and products.

As we were working on solving specific problems for Microsoft products, we also wanted to get our tools directly into the hands of our customers. Making usable tools requires more than just clever algorithms: we need to consider the end-to-end user experience. We added predictive analytics to the Commerce Server product in order to provide recommendation service to our customers. We shipped the SQL Server Data Mining product in 2005, which allowed customers to build analytics on top of our SQL Server product.

Read more about it here.

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