Since the launch of Azure Machine Learning, there have been a lots published on how to get started with AML looking at basic regression, while regression is great, it only skims the surface of what machine learning is good at. In this session we go beyond the basics of regression and look at how we can clean and tune our model to boost its predictive performance. We will look at what you model is actually telling you and investigate how we can improve your accuracy. We will look at what algorithm works for what type of scenario, whether you're looking to predict, classify, recommend, cluster or segment. We will also look at why they work and what they are doing and how we can tweak their parameters to boost performance of our model. This is not Machine learning out of the box, this is applied machine learning.

Is this session for you? Terms like supervised, unsupervised learning, confusion matrix, area under the curve should be familiar to you, however you might not be familiar with how these values are calculated. That is ok. We will look at each of these.