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Optimization adjusts weights to reduce mistakes and raise accuracy.
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Sensors and code adjust motors to prevent falling.
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A model is what the computer builds after training so it can recognize patterns or predict results.
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The algorithm slowly changes weights in the direction that lowers error.
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Robots compute steps to reach destinations efficiently.
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Accuracy measures how often predictions match real answers.
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Robots record obstacles to navigate later.