Supervised Learning

Learn from labeled examples (input + correct output).

Unsupervised Learning

Find hidden patterns or structures in data without labels.

Learn by interacting with an environment and receiving rewards or penalties.

Create new data that resembles training data.

Infer new information, solve problems, or apply logical rules.

Train on huge amounts of data to adapt to many tasks (fine-tuning or prompting).