Machine Learning can be confusing sometimes.
From the esoteric terms to elevated expositions it seems like a terribly difficult area to get into.
Seth Juarez, like me, started off as a developer, and he tackles the one term that is used all of the time in Machine Learning: the elusive “model.
From the description:
First we set up how machine learning is different, how to think about it, and finally what a model actually is (spoiler alert – think “a function written a different way”). Would love your feedback