Titanic Survival Predictor

This project is a machine learning application that predicts the survival probability of Titanic passengers.

Features

• User-friendly interface built with Streamlit
• Prediction using Logistic Regression model
• Real-time prediction results

Installation

1. Install required packages:

pip install -r requirements.txt

2. Train the model:

python model.py

3. Run the application:

streamlit run app.py

Usage

When the application starts, you can enter the following information:

• Passenger Class (1, 2, or 3)
• Sex
• Age
• Number of Siblings/Spouses Aboard
• Number of Parents/Children Aboard
• Fare Paid
• Port of Embarkation

Click the "Predict" button to see the survival probability prediction.

Dataset

The project uses the Titanic dataset from Kaggle. The dataset includes the following features:

• Pclass (Passenger Class)
• Sex
• Age
• SibSp (Number of Siblings/Spouses Aboard)
• Parch (Number of Parents/Children Aboard)
• Fare
• Embarked (Port of Embarkation)

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