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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. This is often referred to as prediction or deployment. For example, if you train a model to classify images, the inference phase is when you feed a new image into that model to get a classification label. Another key aspect of inference is applying the learned parameters (weights and biases) from the model to the input data to produce an output