Anomaly detection is a crucial technique in various fields, and its importance stems from the need to identify unusual or abnormal instances within datasets.

There are many sectors where anomaly detection is important to use. Sectors such as: Fraud Detection, Security, Healthcare, Manufacturing and Industry, Energy Management, Environmental Monitoring, Market Trends.

In the following Jupyter Notebook, it will be presented a list of anomaly detection techniques that are widely used in Data Science, Approaches from Time Series, Data Mining, Machine Learning and Statistics.

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