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wisdm's Introduction

Synopsis

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.

Prerequisites

You need:

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

Running

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.

Motivation

This notebook is intended as a tutorial.

License

Files shared under the MIT License.

Other links

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

wisdm's People

Contributors

samastro avatar

Stargazers

Keyi Li avatar Jakub Dybczak avatar Polly Hsieh avatar

Watchers

James Cloos avatar  avatar

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