I am trying to use Machine Learning to predict the load of a residence at any point in time for a whole year. I have past data pertaining to that house. So I have the training data and I need the algorithm to predict future loads of the house.
Based on my knowledge, I have found the "supervised" machine learning technique to be the one I must adapt. I figured this out since I have labelled test data, I have a prediction requirement and I can get feedback for my prediction (cross-checking with the actual value). Am I correct here?
Also, I read online that "Unsupervised" learning is to be used at places where we need to find "Hidden data structure". I assume it means pattern. If so, what is the difference between the unsupervised and supervised learning in my case. Both of them will give me a prediction about the future load pertaining to that house at any point in time.
I am doing my Masters in EE (Power systems). I am new to Machine Learning as well.