Answer Posted / Vipin Kumar Kushwaha

A Training Set is a collection of data used for training a machine learning algorithm. It consists of input features (also known as independent variables) and their corresponding labels or outcomes (dependent variables). On the other hand, a Test Set (or Validation Set) is a separate set of data used to evaluate the performance of the trained model on unseen data.

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