This repository demonstrates using a Long Short-Term Memory (LSTM) Recurrent Neural Network to recognize human activities from smartphone sensor signals. The model takes raw accelerometer and gyroscope data as input and classifies movements into six categories without requiring manual feature engineering, unlike traditional signal processing approaches. The project uses TensorFlow as the deep learning framework and is implemented in Jupyter Notebooks.