What is anomaly detection in time series data?

What is anomaly detection in time series data?

Anomaly detection in time series data involves identifying unusual patterns or outliers that deviate from expected behavior.

Why is it important to detect anomalies in time series?

Detecting anomalies is crucial for identifying potential issues, improving system reliability, and making informed decisions.

Can you give me some examples of where this is used?

Sure! It's used in finance for fraud detection, in manufacturing for equipment failure prediction, and in healthcare for monitoring patient vitals.

What techniques are commonly used for anomaly detection?

Common techniques include statistical methods, machine learning algorithms, and deep learning approaches like LSTM networks.