In machine learning, an algorithm is the underlying set of mathematical rules or procedures that the training process follows to analyze the data and adjust parameters. It describes how learning happens. The dataset is the input the algorithm examines, the trained model (often saved as a file) is the output produced after the algorithm finishes learning, and a hosted endpoint is merely an infrastructure resource used to serve predictions, not part of the learning strategy itself.
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Fundamentals of AI and ML
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