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Anomaly Detection with StatsForecast and PyMC

Data is like garbage. You’d better know what you are going to do with it before you collect it.

– Mark Twain

In the diverse ecosystem of data analysis, one of the most intriguing yet complex areas you will encounter is anomaly detection. It’s a challenging task but crucial, as anomalies often signify critical events, such as potential fraud, system errors, or business trends that could impact decision-making.

Throughout this chapter, we’ll navigate through the intricacies of identifying these anomalies, honing our focus on how to handle different data types, including low-frequency data. Our exploration will range from understanding the fundamental nature of an anomaly to implementing a variety ...

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