Clone the repository
git clone https://github.com/ahany42/Titanic-Kaggle-Competition.git
cd Titanic-Kaggle-Competition

Create a virtual environment
python -m venv venv
source venv/bin/activate (On Windows: venv\Scripts\activate)

Install dependencies
pip install -r requirements.txt

Check out the Titanic Notebook: titanic-competition.ipynb for insights into the dataset, missing values, and feature engineering.

To run the notebook, open Jupyter and execute the cells in titanic-competition.ipynb.

To generate predictions for submission:

1. Run the entire notebook.
2. Save the final predictions as submission.csv.
3. Upload submission.csv to Kaggle.

• Best model: Naïve Bayes
• Best accuracy: 82.68%

• Handling missing values in the dataset.
• Encoding categorical features for better model performance.
• Comparing multiple models to find the best-performing one.

Feel free to fork this repo, open issues, or submit pull requests if you have suggestions!

This project is licensed under the MIT License - see the LICENSE file for details.

🚀 Let's win this Kaggle competition! 🏆