Scikit-Learn is one of Python's most popular machine learning libraries, offering a consistent API for dozens of algorithms.

Typical workflow:

1. Load data
2. Split into training and test sets
3. Train the model
4. Evaluate performance
5. Make predictions

Example models include:

• Linear Regression
• Decision Trees
• Logistic Regression

Evaluation metrics such as accuracy, RMSE, and F1 score help determine how well a model generalises to new data.