Achieved ~94% accuracy in predicting a person's activity state based on smartphone accelerometer and gyroscope data. Transformed 561 features into PCA component of 175 features which was used to train a Linear Support Vector Machine in Python using Sklearn.
Download the dataset from https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones