KaggleX Final Project Presentation with Disleve Kanku | Kaggle

About the project: The project focuses on leveraging machine learning and deep learning techniques to identify and classify arrhythmias within ECG data. By using the MIT-BIH Arrhythmia Database, we have analyzed a collection of ECG recordings and categorized them into five classes, including normal rhythms and various arrhythmias. Our work involves data preprocessing, feature engineering, and model training using artificial neural networks, recurrent neural networks (LSTM), and convolutional neural networks (CNN) as well as machine learning models such as rancom …

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