First thing to understand is that “machine learning” is a collection of methods which only have the goal in common. And that goal is to classify new stuff based on known stuff. The actual method, and thus the math, vastly differs depending on what you want to do.
But from my experience learning ML, the most important concept to grasp are matrices. They’re just very convenient to represent calculations on massive amount of multi-dimensional data in a compact mathematical formula.
So my advice if you want to properly understand ML is to start with a linear algebra course. Doesn’t need to be a overly detailed one either.
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