Supervised Learning
Supervised learning is a type of machine learning where the algorithm learns from labeled data. In supervised learning, the input and output variables are known, and the algorithm learns to map the input to the output by minimizing the error between the predicted and actual output. The labeled data is used to train the algorithm, and once the algorithm is trained, it can be used to predict the output for new, unseen data. Supervised learning is used in a variety of applications, including image and speech recognition, natural language processing, and predictive modeling.
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