Supervised Learning Algorithms

Supervised learning is the most common type of machine learning. This comprehensive session covers:

- The theory behind supervised learning
- Classification vs. regression problems
- Key algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forests, and SVMs
- Evaluating model performance with appropriate metrics
- Handling overfitting and underfitting
- Hyperparameter tuning
- Practical implementation in scikit-learn

This workshop includes hands-on exercises to implement and compare different supervised learning algorithms.