For my students I want to make a generic raw data Keras classification model that they can use for any/many combinations of sensor data. Assume uploading, labelling etc of the data is worked out, my question for @louis @aurel or anyone is. The standard Keras classification default model is:
Input–> 20 dense neuron layer -->10 dense neuron layer → Output.
Anyone have an expert mode working Keras classification model that will cover many different types of sensor inputs? I am fine my students adding or reducing layers, just want a more flexible starting point. Any suggestions?
My students might have projects where the sensors are: (or any combination of the sensors I teach )
5 flexible sensors.
Pixy2 Camera which an give shade, x, y, width, height and a few other data points.
temperature, humidity, light, wind speed…
2-4 various air quality sensors such as CO2, VOC, Ozone
motion (x, y only) with several touch sensors
GPS with Acceleration
If raw data to Keras classification is the wrong starting point can someone suggest a better model?