A SkillsCast for this session is not available.
Sadly, you do not live in a perfect world and sometimes you will be forced to make a decision where there is a large degree of uncertainty. In this tutorial, Gary will teach you how to apply the Bayesian principles of machine learning in order to arrive at the best possible decision, by calculating the probability of events happening in an uncertain world. He’ll concentrate on decisions like, should you bet on Tiger Woods to win the Open? Is the mortgage rate likely to go up or down in the next quarter, and should you learn Go, or Rust?
The labs can be completed using either Excel or Python notebook, either via Anaconda installed locally, or a cloud based service such as Azure Notebooks. Attendees should come with/install their preference.
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Tutorial: Bayesian Decision Making in The Face of Uncertainty
Gary Short is a freelance data scientist. He specialises in machine learning and predictive analytics on the Azure Platform, but has an interest in cloud scale analytics in all forms, especially computational linguistics and social network analysis.