Training a dataset other than image

I am in DLS-Course2 right now and from what I understand, most of the training examples are image classifiers. However, I would like to know on the following -

  • What if the training dataset is data fed by sensor( let’s say data sent by sensor is in mV (milli volts) form) along with other parameters which are also scalar. How will the data modeling be for this set of data?

Maybe what i am confused about is my understanding on how does one select input parameters to train the model (if the example is not an image) ?

Sorry, if my question is naïve, but it would be really helpful if you could give some hints/tips here.

Thank you.