August 2018
Intermediate to advanced
378 pages
9h 9m
English
To close the chapter, we will discuss a more realistic use case for neural networks. We will use a public dataset by Anguita, D., Ghio, A., Oneto, L., Parra, X., and Reyes-Ortiz, J. L. (2013) that uses smartphones to track physical activity. The data can be downloaded at https://archive.ics.uci.edu/ml/datasets/human+activity+recognition+using+smartphones. The smartphones had an accelerometer and gyroscope from which 561 features from both time and frequency were used.
The smartphones were worn during walking, walking upstairs, walking downstairs, standing, sitting, and lying down. Although this data came from phones, similar measures could be derived from other devices designed to track activity, ...
Read now
Unlock full access