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AI & Machine Learning · Foundational

Model Training

The process of fitting a model's parameters to data by optimizing an objective function.

Definition

Training repeatedly feeds batches of data through the model, computes a loss, and updates parameters via an optimizer such as gradient descent. It continues for a set number of epochs or until validation performance stops improving. Training is far more compute-intensive than inference.

Exam tip

Training is the compute-heavy phase; inference is the serving phase. Know which phase a scenario describes.

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