Titanic Survival Prediction

Welcome to the Titanic Survival Prediction project! This web application predicts whether a passenger would have survived the Titanic disaster based on their personal details and ticket information.

Live Demo

Access the deployed application here: Titanic Survival Prediction

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Features

• User-Friendly Interface: Input passenger details like Age, Gender, Ticket Fare, etc., to get a survival prediction.
• Machine Learning: Powered by a Decision Tree model for predictions.
• Deployed on Render: Easily accessible on the web.

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How It Works

1. Input Fields:

   • Enter relevant details such as:
     • Age
     • Gender
     • Fare
     • Pclass (Passenger Class)
     • Embarked (Port of Embarkation)
     • Other features from the Titanic dataset.

2. Prediction:

   • Submit the form to get a prediction on whether the passenger would survive (Survived) or not (Did Not Survive).

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Technical Details

• Model:
  • The prediction model is built using a Decision Tree algorithm, trained on the Titanic dataset from Kaggle.
• Backend:
  • Developed using Python and Flask.
• Frontend:
  • Simple and responsive HTML/CSS for a user-friendly experience.
• Deployment:
  • Hosted on Render.

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How to Use the Application

1. Open the live demo.
2. Fill out the form with the requested passenger details.
3. Click the Predict button to see the survival prediction.

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Project Setup (For Local Development)

If you'd like to run the project locally:

1. Clone the repository:

   git clone https://github.com/RehanTaneja/titanic-prediction.git
   cd titanic-prediction

2. Install Dependencies:

   pip install -r requirements.txt

3. Run the application:

   python app.py

4. Open the app locally at http://127.0.0.1:5000.