Abstract:

Machine learning and statistical modelling allows us to answer questions such as:
Whats the likelihood that this user will buy from our website?
When will this mechanical part occur a critical failure?
Whats the credit risk of this customer?
This overview session will introduce you to Microsoft Azure Machine Learning (maml) and discusses how to implement predictive models -- from access to data sources, data exploration, building training and testing sets, machine learning over data, model evaluation and experimentation and finally deploy the model as a service.

About Shawn:
http://blogs.msdn.com/scicoria

@cicorias
Shawn is part of Microsofts technical evangelism and development team (TED) on strategic engagements. Working on leading edge apps and services that showcase the Microsoft platfom - focusing on cloud. Having been around distributed systems for most of his career, started focusing on cloud 2009 - mostly to get things done faster.

Shawn's been a cook, a Blackjack dealer, securities finance trader, developer, manager, architect, trainer, at a bunch of places; had been in consulting services for 10+ years. Also has worked at Citibank, Bankers Trust, Smith Barney, Swiss Bank, SunGard, and State Street. A Software Craftsman at heart.

Event agenda:

6:30 - 7:00pm: Networking & setting up
7:00 - 8:30pm: Workshop
8:30 - 9:00pm: Socializing