Anomaly Detection Tutorials - Machine Learning and Its Types With Implementation

This course on anomaly detection covers the technique of identifying rare events or observations that differ statistically from the rest. The learning outcomes include understanding anomaly detection, implementing Isolation Forest for anomaly detection, using DBScan clustering for anomaly detection, and implementing Local Outlier Factor for anomaly detection. The course teaches practical implementation of these techniques. The intended audience for this course is individuals interested in machine learning, anomaly detection, and data science.