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## What you'll find here The engineered features in the numpy array are the Fast Fourier Transform of the accelerometer data.
The classes (labels) in the numpy array are left-right, up-down, and circle, corresponding to the type of motion made with the smartphone.
A visual example of the feature extraction is available as a screenshot in this folder.
To see the feature extractions of other samples, view the project on edge impulse here.
The neural network is included as a tflite model and h5 file. There is also a notebook for the creation of the model.
The k-means anomaly detection model is also included as a JSON file. A visualization of the anomaly detection model's generated clusters is also included in the folder.
The training data is available on the edge impulse page.
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