This is my Jupyter notebook reproducing the [WISDM: WIreless Sensor Data Mining] (http://www.cis.fordham.edu/wisdm/index.php) data analysis, described in the paper Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). Activity Recognition using Cell Phone Accelerometers, Proceedings of the Fourth International Workshop on Knowledge Discovery from Sensor Data (at KDD-10), Washington DC, found here. It runs with a Python 3.x kernel.

You need:

• Jupyter
• Python 3.x
• the paper data here
• A couple of Python lib :
  • Numpy
  • Sklear

To run the notebook, you need Jupyter installed with a Python 3.x kernel. Then just run

> jupyter-notebook-3.x reproducing_wisdm_data.ipynb

in the correct directory.

This notebook is intended as a tutorial.

Files shared under the MIT License.

link to the Kaggle 'human activity recognition with smartphones' database