Automated Anomaly Detection
Implement automated anomaly detection systems using statistical methods, isolation forests, autoencoders, and real-time detection pipelines.
Course Lessons
Follow these lessons in order for the best learning experience, or jump to any topic you need.
1. Anomaly Detection Overview
Learn about anomaly detection overview in the context of automated anomaly detection. Hands-on examples and best practices.
2. Statistical Methods
Learn about statistical methods in the context of automated anomaly detection. Hands-on examples and best practices.
3. Isolation Forest and LOF
Learn about isolation forest and lof in the context of automated anomaly detection. Hands-on examples and best practices.
4. Autoencoders for Anomalies
Learn about autoencoders for anomalies in the context of automated anomaly detection. Hands-on examples and best practices.
5. Time Series Anomaly Detection
Learn about time series anomaly detection in the context of automated anomaly detection. Hands-on examples and best practices.
6. Real-Time Detection Pipelines
Learn about real-time detection pipelines in the context of automated anomaly detection. Hands-on examples and best practices.
7. Alert Fatigue Reduction
Learn about alert fatigue reduction in the context of automated anomaly detection. Hands-on examples and best practices.
Lilly Tech Systems