Shobha
The best way to predict the future is to invent it
How would you apply cross-validation techniques in a deep learning model?
Cross-validation splits the dataset into training and validation subsets to assess model performance on unseen data. Common techniques include k-fold cross-validation, where the dataset is divided into k parts, and the model is trained and validated k times, each time using a different fold as the validation set.For example, In a 5-fold CV, the dataset is split into 5 parts, and the model is trained 5 times, rotating the validation fold.