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