Inference refers to the process of using a trained model to make predictions on new, unseen data. The process involves applying the learned parameters of the model to new inputs in order to predict the corresponding outputs.
Learning refers to the process of updating the parameters of a model based on the training data. During learning, the model is optimized to minimize a certain loss function on the training data, and the parameters are adjusted in order to improve the model's performance on the task at hand.
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