Give me an example of supervised learning and another for unsupervised learning?
Here I usually expect to hear the 3 words: Classification, Regression, and clustering. These are some of the most popular and basic uses for Machine Learning.
Classification and Regression mainly use supervised learning, and the candidate can give an example showing how historical data is used to train the model.
For example, if someone steals your credit card and makes an online transaction. You will probably get an email or text from your bank asking to verify this transaction. Otherwise, the bank will consider it fraud. Your bank’s algorithm learned your credit card purchasing habits through your purchase history, and when an abnormal transaction was detected, the bank suspected it’s a fraud. This is a form of Machine Learning, and probably it’s decision tree Classification.
Another example is a car company trying to predict sales for next year based on this year’s numbers and historical data, which is a form of Machine Learning and could be linear Regression.
Clustering mainly uses unsupervised learning where there is no historical data. A simple example is the spam email filter where the algorithm examines different parts of all incoming emails, group them together, then cluster the emails into spam and ham.
