Introduction to Anomaly Detection for Engineers

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. This is important for applications like predictive maintenance but can be hard to achieve by inspection alone. Machine learning and deep learning (AI) techniques for anomaly detection can uncover anomalies in time series or image data that would be otherwise hard to spot. Learn how and why to apply anomaly detection algorithms to identify anomalies in hardware sensor data. Check out these other links: - What Is Anomaly Detection?: https://bit.ly/3Re46SO - What Is Automated Visual Inspection?: https://bit.ly/3fn3LQj - Time Series Anomaly Detection Using Deep Learning (Example): https://bit.ly/3BFY6MS - Want to see all the references in a nice, organized list? Check out this journey on Resourcium: https://bit.ly/3SrCI4Y 00:00 What is Anomaly Detection? 01:17 What is Anomaly Detection Used For? 03:10 How Anomaly Detection Works 03:47 Machine Learning Techniques for Time Series Data 05:00 Applying Autoencoders to Hardware for Anomaly Detection 08:55 Training and Testing Algorithms on Hardware