What is the difference between supervised and unsupervised learning in AI, and what are some common applications of each?

Supervised learning and unsupervised learning are two fundamental categories of machine learning techniques used in artificial intelligence (AI) applications. Supervised learning is a type of machine learning in which the algorithm is trained on labeled data. The labeled data has input features (predictor variables) and output labels (response variables). The algorithm learns to map the input features to the output labels by minimizing the error between the predicted and actual labels. Supervised learning is useful in cases where we have a specific outcome in mind and need the algorithm to learn how to produce that outcome. Common applications of supervise....