Supervised Learning
Supervised Learning Tasks
Regression: Used when the target variable is continuous (e.g., predicting house prices or stock market returns).
Regression: when the target variable we wish to predict is continuous - usually numeric.
Examples:
- House Prices (in dollars)
- Life Expectancy (in years)
- Employee Salary (in dollars)
- Distance to the Nearest Galaxy (in light years)
Classification: Used when the target variable is categorical (e.g., determining whether a transaction is fraudulent or not).
Classification: when the target variable we wish to predict is discrete - usually binary or categorical.
Examples:
- Spam or Not (binary)
- Success or Failure (binary)
- Handwritten numeric digits (categorical)
- 1-5 star rating scale (categorical???? )