ProLesson 3 of 37 min read

How gradient descent finds a good model

See how a model improves step by step by measuring its error and moving its parameters downhill.

So far we have said a model learns by adjusting its numbers. But how does it know which way to adjust them? For a huge share of modern machine learning, including neural networks, the answer is an idea called gradient descent. Once you understand it, much of the field becomes less mysterious.

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Written with AI help. Spotted a mistake? Tell us.