SpaceShip Titanic Project

Abstract

The Spaceship Titanic project aims to develop a Machine Learning model to predict the chance of a space traveler being transported to a different dimension based on the passenger’s information. Currently, this model is trained on the passenger data features provided in the Kaggle competition - Spaceship Titanic, and can only consider these features to make a prediction. Based on provided passenger data we can predict a passenger's chance to be transported to a different dimension with 81% accuracy. Compared to other models in Kaggle, based on accuracy our model ranks 80th in thousands of submissions. This Machine Learning Model development process can be extended to other Machine Learning datasets containing information on travel accident victims.

Model used in Deployment

Model	Accuracy	Precision	Recall	F1-Score
Xgboost	0.81	0.81	0.81	0.81

Machine Learning code

Please check the MachineLearningCode folder for Machine Learning code.

Deployment code

Please check the DeploymentCode folder for server code and deployment configuaration.

Relevant Past work

1. 🚀Spaceship Titanic |📊EDA|Feature Engineering✅|
2. 🚀 Spaceship Titanic: A Complete Guide 🏆
3. 🚀Spaceship Titanic: ~81% Easy to understand🚀
4. Among the Elite 🛸 Top 100 Spaceship Titanic
5. 🚀Spaceship Titanic -📊EDA + 27 different models📈

Contributors

1. Farhan Ar Rafi - Project Manger + Developer - LinkedIn
2. Avijeet Shil - Lead + Developer - LinkedIn
3. Naga Sai Sivani Tutika - Developer - LinkedIn
4. Abdul Azeem Mohammed - Developer - LinkedIn
5. Mohd Abdul Quavi Latifi - Developer - LinkedIn

Acknowledgement

If I have seen further it is by standing on the shoulders of Giants - Issac Newton

1. A lot of code in this project has been taken from projects on Kaggle and elsewhere. We have added the ones we remember. If you want us to acknowledge something, please raise an issue in the project.
2. Cover Image is taken from Kaggle.