by-Md Rabiul Islam, PhD Student, TAMU.

Assalamu Alaikum. A CNN-LSTM and attention based efficient hybrid model is developed to classify 5 classes of arrhythmias using single-lead ECG signals. The model achieved 99.12% accuracy with a macro F1 score of 94.39% using MIT-BIH public dataset.

1. Part A: Installing Packages and Basic Visualization of ECG
2. Part B: Denoising, R-Peak Detection, Segmentation
3. Part C: Dataset Loading
4. Part D: Train-Test Splitting and Class Balancing
5. Part E: Model Building and Training
6. Part F: Results

The complete code is given in the Arrhythmia Classification Full and Final Code.ipynb file. Thank you. Bye.