Papers by “Situation Publishing”

Deploying machine learning models the serverless way

– Join the MCubed webcast for tips on getting Machine Learning production-ready without breaking the bank

Machine learning disciplines with insane amounts of parameters currently get practitioners swooning when it comes to precision.

December 2021

Building Trust and Confidence in AI

– Things to keep in mind when baking explainability into your AI systems

Machine learning and AI systems are often described as black boxes: you feed them data, something happens, you get a result.

November 2021

Where to start? Continuous Delivery for Machine Learning

– Face the challenges of real-world ML systems with the MCubed webcast Ep2

In the second installment of our MCubed webcast series, automation expert Danilo Sato will walk you through the components of a good continuous delivery system and help you understand what is necessary to provide users with a stable, current ML application that makes use of all the latest assets.

October 2021

One for your machine learning toolkit

– Benford’s Distribution

In part one of our MCubed webcast series, Prof. Mark Whitehorn will outline what a Benford’s distribution looks like (obviously!) but, more importantly, will explain WHY this distribution occurs. It is vital to understand this because that knowledge allows you to decide whether the pattern is expected in a given set of data. If it is, then “nothing to see here, move along.” If it isn’t, further investigation may well yield fascinating insights (and put fraudsters in jail).

September 2021