Azure Machine Learning: From Design to Integration
Machine Learning is a subfield of computer science concerned with systems that learn from data. So this isn’t about systems that follow explicitly programmed instructions, but rather about systems that find patterns and trends within datasets, and use them to deliver insight and predictions. In this session, you will learn how an Azure Machine Learning solution comes to life: From the creation of a workspace, to the preparation of data, to experimentation with Machine Learning algorithms, and then finally to the integration and embedding of predictive insights into applications. This session has been specifically designed to describe Machine Learning fundamentals, and to help enable and inspire existing data professionals taking their first steps to leverage cloud-based predictive models delivered with Azure Machine Learning. It is guaranteed to thrill you with potential, and excite you with the relative ease by which it can be accomplished.
Peter Myers is a consultant, trainer and presenter, and has worked with Microsoft database and development products since 1997. Today he specializes in all Microsoft Business Intelligence products and also authors training course content for Microsoft products and services. He has a broad business background supported by a bachelor’s degree in applied economics and accounting, and he extends this with extensive experience backed by current MCSE certifications. He has been a Data Platform MVP since 2007.
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