MACHINE LEARNING FOR DETECTING ANOMALIES IN YOUR DATA

As the volume of data generated increases, the effectiveness of manually searching and visualising data to gain insights becomes more and more difficult. An alternative approach is to use machine learning to automatically build behavioural models. These models enable users to gain deep insights into behavioural characteristics that are beyond the capabilities of classical search techniques.

Typical use cases include, automatically understanding systems that are behaving unusually and understanding the typical behaviour of a population. This is a challenge commonly seen in the IT Operations environment and where Security Analytics is top of mind.

This talk will present real examples of machine learning techniques applied to real-time behavioural data, and describe the methodology behind these methods along with an overview of the machine learning space.
 

This lecture is made possible by Anchormen.