Titanic Survival Prediction 🚢

This project predicts whether a passenger survived the Titanic disaster using machine learning.

📁 Project Structure

🔧 Tools Used

• Python
• Pandas, NumPy
• Seaborn, Matplotlib
• Scikit-Learn (RandomForest)

📊 Workflow

1. Data cleaning and feature engineering
2. Model training (RandomForest)
3. Model evaluation (accuracy: ~82%)
4. Confusion matrix and classification report

🚀 How to Run

1. Clone the repo:

   git clone https://github.com/your-username/Titanic-Survival-Prediction.git
   cd Titanic-Survival-Prediction
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the notebook:

   jupyter notebook notebooks/titanic_eda_model.ipynb
   

📈 Model Accuracy

• Accuracy: ~82%
• Classifier: RandomForest
• Features: Pclass, Sex, Age, Fare, FamilySize, etc.