In this project, I analyzed the Titanic dataset to predict passenger survival.
- Data Exploration: Investigated the dataset to identify key features and uncover patterns.
- Data Cleaning: Addressed missing values and prepared the dataset for analysis.
- Feature Engineering: Processed categorical variables and scaled numerical features to enhance model performance.
- Modeling: Developed and optimized a Random Forest model.
- Visualization: Created insightful visualizations to illustrate data trends and model performance, including ROC curves and confusion matrices.
Achieved an accuracy of 0.83.