Supervised learning is the machine learning scenario in which one or more data points from a set of data points is/are associated with a label. The model then learns to predict the labels for unseen data points. For our purposes, each data point will normally be a tensor and will be associated with a label. Supervised learning problems abound in computer vision; for example, an algorithm is shown many pictures of ripe and unripe tomatoes, together with a categorical label indicating whether or not they are ripe, and when the training has concluded, the model is able to predict the status of tomatoes that weren't in its training set. This could have a very direct application in a physical sorting mechanism for tomatoes; or an algorithm that could learn to predict the gender and age of a new face after it has been shown many examples, together with their...
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