Philipp is part of the infrastructure team and a developer advocate at Elastic. He is frequently talking about full-text search, databases, operations, and security. Additionally, he is organizing multiple meetups in Vienna.
Machine Learning without the Hype
Machine learning is both a highly overloaded and hyped topic. This talk covers one specific area in this space — anomaly detection of time-series data. It sounds very narrow, but is widely applicable in IT security and operations. In particular we take a look at: What is artificial intelligence, machine learning, and deep learning mean in general? When is a rule-based approach the right solution and when do you need machine learning? What does machine learning mean for time-series data? What is the difference between supervised and unsupervised learning in this area? What could an example with an actual dataset look like?
