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?