Use real-world Electrocardiogram (ECG) data to detect anomalies in a patient heartbeat. We’ll build an LSTM Autoencoder, train it on a set of normal heartbeats and classify unseen examples as normal or anomalies.

⭐️ Tutorial Contents ⭐️

(04:35​) Load the ECG data
(14:09​) Exploratory Data Analysis
(23:29​) Data preprocessing
(33:30​) Build an LSTM Autoencoder with PyTorch
(43:07​) Training
(50:58​) Loading pre-trained model
(51:53​) Choosing a threshold for anomaly detection
(55:36​) Finding abnormal heartbeats

Complete tutorial + source code:…



#pytorch #python

Time Series Anomaly Detection Tutorial with PyTorch in Python | LSTM Autoencoder for ECG Data
8.10 GEEK