Anomaly Detection Workloads

The video tutorial explains anomaly detection, a process to identify unexpected values or events using AI and machine learning. It covers how anomaly detection works by analyzing data over time to determine expected value boundaries. Examples include credit card transactions and IoT sensors in racing cars. The tutorial also discusses true or false statements about anomaly detection, such as its ability to work in real-time, analyze historical data, and enable preemptive actions. The concept of anomaly detection is clarified through various examples and explanations.

Explain how machine learning models can detect anomalies in historical data.

What is the significance of preemptive action in anomaly detection?

Why is it incorrect to say that anomaly detection predicts when a problem will occur?