Supervised learning is a type of machine learning where the algorithm is trained on a labeled dataset, meaning that the input data is paired with corresponding output data. The goal of supervised learning is to learn a mapping function from the input to the output based on the labeled examples. This learned function can then be used to make predictions on new, unseen data. Supervised learning is commonly used in a variety of applications, such as image recognition, speech recognition, and natural language processing. It is a powerful tool for making predictions and automating decision-making processes.
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