Explore advanced anomaly detection techniques for embedded machine learning in this tinyML talk. Learn to implement custom DSP blocks for IoT data analysis, leverage feature importance to focus on key frequency bands, and optimize anomaly detection thresholds. Discover how to create effective models for classifying anomalous sensor readings using Edge Impulse's powerful features. Gain insights into data-driven engineering for dataset creation, and understand various applications from cold chain monitoring to fault detection in industrial machinery and satellites. Dive into topics such as impulse design, neural network classification, live classification, and deployment options. Master the use of tools like Feature Explorer, Anomaly Explorer, and EON Tuner to enhance your anomaly detection capabilities on constrained always-on devices.