Supervised Learning Quiz

What you'll be asked

1. In the context of supervised learning, what is the primary purpose of the 'label' in a dataset?
2. Which of the following scenarios is a classic example of a classification problem in supervised learning?
3. What is the main difference between regression and classification tasks in supervised learning?
4. If a model performs exceptionally well on the training data but fails to generalize to new, unseen data, what is the most likely issue?
5. When training a supervised model, why is it critical to keep a 'test set' that is completely separate from the 'training set'?

Answers and explanations come after you submit.