An interactive Streamlit web application that predicts passenger survival on the Titanic using a trained machine learning model.
This project covers the complete ML pipeline — from data exploration, preprocessing, model training, and evaluation to deployment on Streamlit Cloud.
This app allows users to:
- Explore the Titanic dataset interactively
- Visualize survival statistics with dynamic charts
- Enter passenger details and get real-time survival predictions
- View model performance metrics (accuracy, classification report, confusion matrix)
ml-streamlit-project/ │── app.py # Main Streamlit app │── model.pkl # Trained ML model │── requirements.txt # Project dependencies │── README.md # Project documentation │── data/ │ └── train.csv # Titanic dataset │── notebooks/ │ └── model_training.ipynb # Colab notebook for model training