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When I hear "training a model" I translate that to y=mx+c

I think of Y = f(X). f can be anything from tree based model to a neural network to nonparametric model.

Y = Mx + c is simple and common but by no means the only kind of model.

I think what the poster was implying was that most people create simple models, because they have a linear thought process, but they call it a model to sound sophisticated.

I was going for they call it a model to sound sophisticated - they call it training a model when they are really doing a linear regression.

Technically doing a pair of linest in excel and a goal seek to weight the output of each is Ai.

Sometimes the Groundbreaking Ai startup that just raised a gazillion dollars in their 10th up round, is just a plain old basic high school statistical model.

Linear regression is a legitimate model, and fitting its parameters is definitionally machine learning.

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