This project aims to predict the survival of passengers on the Titanic using machine learning techniques. The sinking of the RMS Titanic is one of the most infamous shipwrecks in history, and this project analyzes the Titanic dataset to build a machine learning model that predicts whether a passenger would survive based on various features such as passenger class, gender, age, and more.
The dataset used in this project is sourced from Kaggle's Titanic: Machine Learning from Disaster competition. It contains information about the passengers aboard the Titanic, including features such as passenger ID, survival status, passenger class, name, gender, age, number of siblings/spouses aboard, number of parents/children aboard, ticket number, fare, port of embarkation, and cabin details.
The project structure includes directories such as train.csv
, app.py
, templates/
, static/
. To run the project locally, clone the repository, navigate to the project directory, run the Flask web application using python app.py
. Then, access the application in your web browser at (https://flask-deploy-b45k.onrender.com/)
.
Contributors to this project include Harsha Parida.