Lesson learned

• Using supervised learning techniques to build predictive models
• For both regression and classification problems
• Underfitting and overfitting
• How to split data
• Cross-validation
• Data preprocessing techniques
• Model selection
• Hyperparameter tuning
• Model performance evaluation
• Using pipelines