Supervised Learning is a type of machine learning where the model is trained on a labeled dataset—which means each input has a corresponding correct output. The algorithm learns to map inputs to outputs by identifying patterns in the training data.
It is commonly used for:
- Classification (e.g., spam detection, image recognition)
- Regression (e.g., predicting house prices, stock forecasting)
Supervised learning is ideal when historical data with known outcomes is available and the goal is to make accurate future predictions.
