22-25 April 2026 
SQLBits 2018
Inside the classic machine learning algorithms
Algorithms like Neural Nets, Deep Learning, SVM and KNN are dominating the Machine Learning world. You don’t need to know the maths behind them but you do need to know how they work in order to use them effectively. This talk will explain just that.
Machine Learning is not magic. You can’t just throw the data through an algorithm and expect it to provide insights. You have to prepare the data and very often you have to tune the algorithm. Some algorithms - Neural Nets, Deep Learning, Support Vector Machines and Nearest Neighbour - are starting to dominate the field. A great deal of attention is often focused on the maths behind these, and it IS fascinating.
But you don’t have to understand the maths to be able to use these algorithms effectively. What you do need
to know is how they work because that is the information that allows you to tune them effectively. This talk will explain how they work from a non-mathematical standpoint.
But you don’t have to understand the maths to be able to use these algorithms effectively. What you do need
to know is how they work because that is the information that allows you to tune them effectively. This talk will explain how they work from a non-mathematical standpoint.
Speakers
Mark Whitehorn's previous sessions
Graph databases - What, how and why
Graph databases – Origins, how they work, strengths and weaknesses
Inside the classic machine learning algorithms
Algorithms like Neural Nets, Deep Learning, SVM and KNN are dominating the Machine Learning world. You don’t need to know the maths behind them but you do need to know how they work in order to use them effectively. This talk will explain just that.
Evaluating Models: Get Ready to ROC
Introducing the ROC curve and its use in Azure ML.
Analytics Master Class-exploiting exotic patterns in data
There are some little-known but very useful ways of extracting information from data.
This session will cover:
• Monte Carlo simulations
• Nyquist’s Theorem
• Simpson’s paradox
• Benford’s Law
These will rock your world (they certainly rocked mine).
MDX and DAX-compare and contrast
This talk looks at MDX and DAX, examining their similarities and differences. It won’t turn you into an expert in either but it will help you to decide, given your particular career plans, if either or both are worth learning.