I have a large data set with over 100k samples and I want to predict a continuous target feature from 4 other continuous features using Scikit Learn. For this project, I would like to visualize and analyze the data using both 1 dimensional and two dimensional histograms. I know how to plot histograms and I know what a histogram means/displays mathematically but how can I make good use of it in order to analyze my data?
One thing that comes to mind is that I could spot regions with outliers, but this doesn't seem so useful/efficient (correct me if I'm wrong).
So what are useful ways to use histograms for analyzing Machine Learning data?