This document discusses various techniques for visualizing machine learning data using Python. It describes univariate visualization methods like histograms, density plots, and box plots to understand each attribute independently. It also covers multivariate visualization techniques like correlation matrix plots and scatter matrix plots to understand interactions between multiple attributes. Examples of generating histograms, density plots, box plots, correlation matrices, and scatter matrices on a diabetes dataset are provided to illustrate how to implement these techniques in Python.