This post was inspired by Section 2.3 of the excellent (and free) textbook, The Elements of Statistical Learning (1). The example analyses were done with scikit-learn (2). The data analyzed was taken from Kaggle (3).

When writing this post, I consulted the first 6 hits from Google that were returned when I searched for “How to remember Bayes’ theorem” as well as two books that I had that seemed relevant. All of these resources are listed in references section at the end of the post. Credit for good ideas contained in this post go to the creators of those resources. Any mistakes are mine.

This post was inspired by and draws heavily from the material in the Python Graph Gallery, specifically the page on 2D density plots. I highly recommend checking out that page as well as the other pages on the Python Graph Gallery.

For as long as I can remember, I have been driven by my desire to understand how the world works. One question stuck in my mind during my junior year of high school, “What are the differences between living and non-living things?” It seemed to me that if you knew where all of the atoms were and how the atoms interacted, you should be able to predict the behavior of any physical system and that this should be true of living and non-living things alike. None of these ideas were new, of course. I was beaten to the punch by at least 200 years, but these kinds of questions continue to motivate my intellectual pursuits even today.