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Explain how neural networks learn from data.

Neural networks learn through a process called backpropagation. They adjust the weights of connections between neurons by minimizing error using gradient descent. Each training example teaches the network to get slightly better — iterating millions of times until it captures the underlying pattern in the data.

Can you show me a simple Python example?

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