👉 The validation set is a subset of data used to evaluate the performance of a machine learning model during training, serving as an unbiased measure of its generalization ability. Unlike the training set, which is used to adjust model parameters, the validation set helps tune hyperparameters and monitor overfitting by providing a realistic assessment of how well the model will perform on unseen data. This fluid, dynamic selection process ensures that the final model is robust and capable of making accurate predictions on new, independent data.
