What are the differences between supervised, unsupervised, and reinforcement learning?

What are the differences between supervised, unsupervised, and reinforcement learning?

Supervised learning uses labeled data to train models, while unsupervised learning finds patterns in unlabeled data. Reinforcement learning focuses on training agents to make decisions through trial and error.

Can you give examples of each type?

Sure! For supervised learning, think of image classification. Unsupervised learning could be customer segmentation, and reinforcement learning is often used in game AI, like training a bot to play chess.

How do these learning types apply in real-world scenarios?

Supervised learning is used in spam detection, unsupervised learning in market basket analysis, and reinforcement learning in robotics and autonomous vehicles.

Which type is the most commonly used?

Supervised learning is the most commonly used type, especially in applications like image recognition and natural language processing.