Anomaly Detection Tutorials - Machine Learning and Its Types With Implementation

Explore anomaly detection techniques in machine learning through a comprehensive tutorial covering various types and their implementations. Learn about the concept of identifying rare events or observations that statistically differ from the norm, potentially indicating problems like fraud or system failures. Dive into Isolation Forest, DBScan Clustering, and Local Outlier Factor methods for anomaly detection, with practical implementations demonstrated throughout the video. Gain insights into applying these techniques to real-world scenarios and enhance your understanding of this crucial aspect of data analysis and problem detection.

- What Is Anomaly Detection
- Isolation Forest Anamoly Detection
- Practical Implementation Isolation Forest
- Anamoly Detection Using DBScan Clustering
- DBSCAN Anomaly Practical Implementation
- Local Outlier Factor Anomaly Detection