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#SupervisedLearning is a type of #MachineLearning where an algorithm is trained on a labeled dataset to predict outcomes for new data

The labeled dataset contains input variables and the desired output, and the algorithm uses this information to make predictions
In #SupervisedLearning, the algorithm is constantly adjusting its parameters to minimize the prediction error

One of the most popular algorithms for #SupervisedLearning is #LinearRegression, used for prediction problems where the target is continuous
Another common algorithm is #LogisticRegression, used for classification problems where the target is binary

#DecisionTrees and #RandomForests are commonly used for both regression and classification problems
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