Senior Director, Market Strategy and Intelligence
Come to this session to learn the fundamentals of predictive analytics and see how to make it real in Azure ML.
“Predicting future outcomes through the construction of statistical or heuristic models, based on past observations.” It all sounds very lofty, doesn’t it? And, because of that, maybe it sounds irrelevant to your production work. Throw in newer names like “deep leaning” and even older ones like “artificial intelligence” and the whole discipline can seem downright esoteric and meaningless to your skill set.
But cut through the fancy names and you’ll see that predictive analytics, based on well-documented machine learning algorithms, is useful, approachable and can be very developer-friendly. Azure Machine Learning (ML) ties right into this, providing a visual design canvas for building your models and a straightforward Web API for imbuing your applications with predictive capabilities. Want your applications to predict future revenues, alert users to potential fraud or help determine which consumers are most likely to be high-spending customers? Come to this session to learn the fundamentals of predictive analytics and see how to make it real in Azure ML.
You will learn:
- Learn the fundamentals of predictive analytics, including which algorithms work best for specific scenarios
- Learn how to build Azure Machine Learning experiments and models
- Get exposed to the R programming language and see how to integrate R code into Azure ML experiments