A training step is a single pass where a model processes a batch of data, updates its parameters, and reduces error through backpropagation. Used in machine learning and AI development, it gradually improves accuracy during model training. Data scientists, engineers, and researchers benefit from it, as each step refines predictions and optimizes performance.
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