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Greg Ainslie-Malik

Greg Ainslie-Malik

Greg is a recovering mathematician and part of the technical advisory team at Splunk, specialising in how to get value from machine learning and advanced analytics. Previously the product manager for Splunk’s Machine Learning Toolkit (MLTK) he helped set the strategy for machine learning in the core Splunk platform. A particular career highlight was partnering with the World Economic Forum to provide subject matter expertise on the AI Procurement in a Box project.

Before working at Splunk he spent a number of years with Deloitte and prior to that BAE Systems Detica working as a data scientist. Ahead of getting a proper job he spent way too long at university collecting degrees in maths including a PhD on “Mathematical Analysis of PWM Processes”.

When he is not at work he is usually herding his three young lads around while thinking that work is significantly more relaxing than being at home…

Platform 3 Min Read

Making Smarter Predictions in ITSI

As we are trying to commoditize machine learning through our MLTK smart workflows, this article outlines another example of an MLTK smart workflow, designed to help improve the usability of the predictive capabilities in ITSI.
Observability 6 Min Read

Understanding and Baselining Network Behaviour using Machine Learning - Part II

In this second installment we will continue to use the Coburg Intrusion Detection Data Sets (CIDDS) to determine baseline behaviour for one of the nodes we identified as critical in the first half of this series.
Observability 7 Min Read

Understanding and Baselining Network Behaviour using Machine Learning - Part I

Learn about analytical techniques that help you to better understand your network and develop baseline for network behaviour and detect anomalies.
Platform 5 Min Read

Cyclical Statistical Forecasts and Anomalies – Part 4

Discover an alternative technique of detecting anomalies and creating alerts with the Machine Learning Toolkit.