Machine Learning Algorithms In Layman's Terms, Part 1

As a recent graduate of the Flatiron School's Data Science Bootcamp, I've been inundated with advice on how to ace technical interviews. A soft skill that keeps coming to the forefront is the ability to explain complex machine learning algorithms to a non-technical person. This series of posts is me sharing with the world how I would explain all the machine learning topics I come across on a regular basis...to my grandma. Some get a bit in-depth, others less so, but all I believe are useful to a non-Data Scientist. In the upcoming parts of this series, I'll be going over: "a model is like a Vending Machine, which given an input (money), will give you some output (a soda can maybe) . . . An algorithm is what is used to train a model, all the decisions a model is supposed to take based on the given input, to give an expected output. For example, an algorithm will decide based on the dollar value of the money given, and the product you chose, whether the money is enough or not, how much balance you are supposed to get [back], and so on."