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How Models Learn

We have seen that machine learning models have parameters and that training means finding good values for those parameters. But how does the algorithm actually find them? The answer involves iterative improvement: start with a guess, measure how wrong it is, adjust in the right direction, and repeat.

Training as Iterative Improvement

We have seen that machine learning models have parameters and that training means finding good values for those parameters. But how does the algorithm actually find them? The answer involves iterative improvement: start with a guess, measure how wrong it is, adjust in the right direction, and repeat.