Question 1

What is the difference between supervised and unsupervised learning?

Accepted Answer

Supervised learning involves training a model on labeled data, where the desired output is known. Unsupervised learning involves training a model on unlabeled data to find hidden patterns or structures.

Question 2

What is overfitting and how can you prevent it?

Accepted Answer

Overfitting is when a model learns the training data too well, including its noise, and performs poorly on new, unseen data. It can be prevented by using techniques like cross-validation, regularization, and early stopping.

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