• A machine learning model that classifies yoga poses performed by the user in real-time from a live video feed based on a novel approach I came up with i.e. coordinate-driven classification. • The model has an F1 score of 0.98 and a real-world accuracy of 98%. • My paper comparing this model to other methods of pose classification has been accepted in the International Conference on Electrical Electronics and Computing Technologies (ICEECT) by IEEE. • Built my own dataset containing tens of thousands of dataframes, for the training and validation of the model.