Key Takeaways

• The main goal of Anomaly Detection analysis is to identify the observations that do not adhere to general patterns considered as normal behavior.
• Anomaly Detection could be useful in understanding data problems.
• There are domains where anomaly detection methods are quite effective.
• Modern ML tools include Isolation Forests and other similar methods, but you need to understand the basic concept for successful implementation
• Isolation Forests method is unsupervised outlier detection method with interpretable results.

#2020 dec tutorials # overviews #anomaly detection #machine learning #python #scikit-learn #unsupervised learning