Predicting the survival of passengers aboard the Titanic using machine learning. This project demonstrates data preprocessing, feature engineering, predictive modeling, hyperparameter tuning, and model evaluation. It is designed to be reproducible and beginner-friendly, making it ideal for a data science portfolio.

• Language: Python 3
• Libraries: Pandas, Matplotlib, Scikit-Learn
• Machine Learning: Random Forest Classifier, Grid Search Hyperparameter Tuning
• Evaluation: ROC Curve, AUC, Confusion Matrix

• Engineered a FamilySize feature to improve predictive power
• Achieved 81% accuracy and AUC of 0.88 on test data
• Visualized feature importance to interpret model decisions