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Preprocessing my fall detection dataset using data standardisation and sliding windows, and splitting this data into train/validation/test sets. Modelling performed on PyTorch using LSTM and CNN networks. The final models were exported to `.tflite` files to be run on a mobile phone. The best performing model was the ResNet152 with 92.8% AUC.