As most data scientists will tell you, there is no such thing as the single best model or the perfect model. Some work well in some circumstances but poorly in others, some present a specific tradeoff between factors like flexibility and explainability that is only useful in certain settings. Some are best set up to handle specific types of data that don’t arise in every single project. 

But at the same time, most data scientists would acknowledge that some models manage to stand out. Maybe it’s nostalgia, maybe it’s how powerful they are in some settings, maybe it’s another factor entirely — but for one reason or another, most data scientists will admit they have a soft spot for some models. That’s what we’re here to discuss this month: what is your favorite model? Listen in to hear more about:

• The benefits of simple models
• How learning about some models teaches you about entire fields of mathematics 
• What fitting a classification model has to teach us about epistemology 

For the full show notes, including who's who, see the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Medium writeup⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.