Can you build a classification model with a simple numpy array
Yes, definitely!
After all image is just a 2D array of numbers.
When you build your classification network, or modify an existing one, you just want to design it so the input layer of the neural network will be a simple array of numbers.
If I have to estimate its performance, I would bet on higher performance relative to a conversational image classifier that does the same task, because every bit of input data is relevant and the data will most likely be smaller without losing any details.
I was wondering if I could build a classification model that just works on simple data I for example stock market classification 1 if it goes up 0 of down. I ask because I never see models like this and tutorials only ever with image or text classification and I typically see regression models working with this form of data