This assignment builds a Gradient Boosting Machine (GBM) model to predict exercise performance using wearable sensor data. The data is cleaned by removing missing, low-variance, and non-informative variables, and the model is trained using cross-validation. Model performance is evaluated with a confusion matrix, and final predictions are generated for the test dataset.