Titanic-Classification-DEPI-Mini-Project

Titanic Survival Prediction 🚢

This model predicts whether a passenger survived the Titanic disaster based on features such as age, gender, passenger class, and more.
It was developed as part of the DEPI Mini Project using the Titanic dataset from Kaggle.

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Model Details

• Algorithms used: Logistic Regression, Decision Tree (final model chosen based on performance).
• Frameworks: Scikit-learn, Pandas, NumPy.
• Input features:
  • Age
  • Sex
  • Passenger Class (Pclass)
  • Siblings/Spouses Aboard (SibSp)
  • Parents/Children Aboard (Parch)
  • Fare
  • Embarked

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Intended Use

• Educational purposes: ML pipelines, preprocessing, and model evaluation.
• Demonstrating supervised learning on tabular datasets.

⚠️ Not intended for real-world predictive use — dataset is historical and simplified.

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How to Use

from huggingface_hub import hf_hub_download
import joblib

# Download model from Hugging Face Hub
model_path = hf_hub_download(repo_id="HussienElhaddad/Titanic-Classification-DEPI-Mini-Project", filename="titanic_model.pkl")
model = joblib.load(model_path)

# Example input (Age=22, Sex=male, Pclass=3, etc.)
X_new = [[22, 0, 3, 1, 0, 7.25, 2]]  
prediction = model.predict(X_new)

print("Survived" if prediction[0] == 1 else "Not Survived")