Training data is the collection of examples an AI model learns from during development. Its quality, quantity, and representativeness directly shape how well the model performs and what biases it may pick up. If the data is incomplete or skewed, the model's predictions will reflect those flaws. This is why careful selection and cleaning of training data is a critical part of building reliable AI.
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