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Prediction of the type of physical activity (e.g., walking, climbing stairs) from tri-axial smartphone accelerometer data. The input data used for training in this project consists of two files. The first file, train_time_series.csv, contains the raw accelerometer data, which has been collected using the Beiwe research platform. The second file, train_labels.csv, contains the activity labels. Different activities have been numbered with integers: 1 = standing, 2 = walking, 3 = stairs down, 4 = stairs up. Because the accelerometers are sampled at high frequency, the labels in train_labels.csv are only provided for every 10th observation in train_time_series.csv.
Code for Coursera's Machine Learning and Data Analysis specialization
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