reginald-garnepudi / human_activity_recognition_pytorch

Human Activity Recognition using PyTorch

This is an exercise to implement a few deep learning models for recognising human activities (like walking, standing, etc) from sensor data (accelerometer and gyroscope) collected from mobile phones.

We use Jason Brownlee's tutorial (in Keras) as a source of inspiration and look to implement the models in PyTorch.

Pre-requisites

Python 3.7
Pytorch 1.4
pandas
scikit-learn
seaborn
jupyter

tensorflow 2.1 (if you are running the tensorflow notebook)

How to

• pip install the obove required libraries
• Open terminal and cd to this root folder
• Run jupyter notebook from the root folder
• Open the human_activity_recognition.ipynb notebook
• The notebook is fairly self explanatory.

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