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Supervised learning involves training models using labeled data to predict outcomes, with applications in various fields such as healthcare and finance. Classification and regression are two main types of supervised learning, where classification predicts categorical outcomes and regression predicts numerical values. Key steps in building these models include problem identification, data preprocessing, algorithm selection, and evaluation of model performance.

Author

raghavshrivastav0812

Language

EN