What are the differences between various AI algorithms?

What are the main differences between supervised and unsupervised learning algorithms?

Supervised learning algorithms use labeled data to train models, while unsupervised learning algorithms find patterns in unlabeled data.

Can you give examples of each type?

Sure! For supervised learning, examples include linear regression and decision trees. For unsupervised learning, examples are k-means clustering and hierarchical clustering.

What about reinforcement learning? How does it differ from the other two?

Reinforcement learning focuses on training agents to make decisions by rewarding them for good actions, unlike the other two which rely on data patterns.

Are there any specific use cases for each algorithm?

Yes! Supervised learning is often used in spam detection, unsupervised learning in customer segmentation, and reinforcement learning in game AI.