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In the context of machine learning, **inference** is the process of using a trained machine learning model to make predictions or decisions on new, unseen data. Essentially, once a model has been trained on a dataset, the inference phase is when you feed new input data into that model to get an output.

This process is distinct from the training phase, where the model learns patterns from the data, adjusts its internal parameters (weights and biases), and minimizes a loss function.