Types of Artificial Intelligence (AI) Models

AI Models are not a monolith. From the tiny decision trees in your calculator to the massive LLMs running in global data centers, the architecture defines the capability.

1. Learning Paradigms

Supervised Learning

The 'Teacher' model. Trained on labeled data.

• Key Models: Linear/Logistic Regression, Random Forests, XGBoost.
• Objective: Map $X$ to $Y$ with minimum error.

Unsupervised Learning

The 'Self-Discovery' model. Finds hidden patterns in unlabeled data.

• Key Models: K-Means Clustering, PCA (Principal Component Analysis).
• Objective: Find the structure of $X$.

Reinforcement Learning (RL)

The 'Reward' model. Learns by trial and error in an environment.