The Three Types of ML
Machine Learning is broadly categorized into three distinct methodologies based on how they interact with data.
Supervised Learning
The model learns from labeled data. We give it both the question and the answer until it learns the pattern (e.g., predicting housing prices).
Not all learning is the same. Just as humans learn through classroom instruction, exploration, or trial-and-error, machine learning is categorized into three primary types based on the feedback the system receives during training: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Each type is suited for different kinds of tasks and requires different types of data preparation.
Detailed Classification
1. Supervised Learning: The most common type. Data includes the 'answers' (labels). Used for predicting categorical or continuous values.
2. Unsupervised Learning: No labels. The AI discovers the structure. Used for finding hidden groups or reducing complexity.
3. Reinforcement Learning: Experimental learning. The AI learns from the results of its own actions. Used for robotics and strategy games.