Why Optimization in ML?

How models actually learn, from vanilla gradient descent to Adam

Machine learning looks like prediction, classification, generation, recommendation. Under the hood it is one repeated mathematical act: choose numbers, measure how bad they are, then change the numbers to make the badness smaller. That is optimization.

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▶ Why Optimization in ML?
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