AI Techniques for ECG Classification

Learn the essential aspects of developing machine learning and deep learning models for classifying EKG signals. Explore topics like signal annotation, and see how techniques like wavelet scattering can be used with machine learning and deep learning techniques and automated code generation for deploying these algorithms.

Part 1: Introduction and Data Annotation Explore the tools available for annotating ECG signal datasets to prepare them for AI workflows.

Part 2: ECG Classification Using Machine Learning Learn about ECG signal preprocessing and feature extraction techniques required for developing classifiers using machine learning algorithms.

Part 3: ECG Classification Using LSTMs Learn about long short-term memory networks, the challenges in training such networks, and how you can use these networks to build ECG classifiers.

Part 4: ECG Classification Using Transfer Learning Learn how you can quickly build an ECG classifier using wavelet time-frequency techniques and pretrained convolutional networks.

Part 5: Deploying ECG Classification Using a Transfer Learning Model Learn how to deploy a transfer learning pipeline on NVIDIA Jetson hardware.