Linear Regression
👉 What it is: Basic model that finds a straight-line relationship between inputs (features) and output.
✅ When to use:
- You have simple relationships
- Features are not highly correlated
- You want easy interpretability
🧠 Real-life examples:
- Predicting house price based on size, bedrooms, location
- Estimating salary from years of experience
- Forecasting sales from advertising spend
⚠️ Limitation:
- Breaks when there are too many features or multicollinearity (features highly correlated)