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Cardiac Arrhythmia refers to a condition in which the heart beats irregularly, fast or slow. There are several types of arrhythmia (bradyarrhythmia, premature heartbeat, tachycardia, ventricular fibrillation, etc.). Out of these some can be very dangerous and even life threatening if not treated quickly. In this paper we try to propose a solution for detecting and then classifying various types of arrhythmia. We have used UCI Arrhythmia dataset to train and test our machine learning models.