Microsoft travaillerait sur un projet de moteur de recommandations de contenu pour site Web. Proposé sous la forme d’un service Azure, il serait basé sur des technologies d’apprentissage automatique. Nom de code : Sage. Le service de Microsoft serait proposé en mode cloud, sur Azure et la solution utiliserait la technologie CloudML, ou cloud Machine Learning : un langage, centré sur les problématiques d’apprentissage automatique, également en cours de développement chez Microsoft. (Source)
Microsoft has been on quite a cloud roll lately and today it announced a new cloud-based machine learning platform called Azure ML, which enables companies to use the power of the cloud to build applications and APIs based on big data and predict future events instead of looking backwards at what happened.
The product is built on the machine learning capabilities already available in several Microsoft products including Xbox and Bing and using predefined templates and workflows has been built to help companies launch predictive applications much more quickly than traditional development methods, even allowing customers to publish APIs and web services on top of the Azure ML platform.
Joseph Sirosh, corporate vice president at Microsoft, who was in charge of the Azure ML, and spent years at Amazon before joining Microsoft to lead this effort, said the platform enables customers and partners to build big data applications to predict, forecast and change future outcomes. The product is currently in confidential preview, but Microsoft did mention a couple of examples including Max 451, a Microsoft partner working with large retailers to help predict which products customers are most likely to purchase, allowing them to stock their stores before the demand.
Microsoft Azure | Data driven intelligence
The limit of human understanding is a numbers game. A doctor can only consume so much information on a chart, a business analyst only so many rows, an Operations team only so much sensor and equipment data. With machine learning, computers can approach human performance in perception and understanding across vast amounts of data. Expensive and disconnected tools stood in the way of this innovation, but today Microsoft is democratizing machine learning.
Machine learning today is usually self-managed and on premises, requiring the training and expertise of data scientists. However, data scientists are in short supply, commercial software licenses can be expensive and popular programming languages for statistical computing have a steep learning curve. Even if a business could overcome these hurdles, deploying new machine learning models in production systems often requires months of engineering investment. Scaling, managing and monitoring these production systems requires the capabilities of a very sophisticated engineering organization, which few enterprises have today. Microsoft Azure Machine Learning, a fully-managed cloud service for building predictive analytics solutions, helps overcome the challenges most businesses have in deploying and using machine learning. How? By delivering a comprehensive machine learning service that has all the benefits of the cloud. In mere hours, with Azure ML, customers and partners can build data-driven applications to predict, forecast and change future outcomes – a process that previously took weeks and months.
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