> ####📣 Recommended Competition
> We highly recommend [Titanic - Machine Learning from Disaster](https://kaggle.com/c/titanic/overview) to get familiar with the basics of machine learning and Kaggle competitions.
Welcome to the year 2912, where your data science skills are needed to solve a cosmic mystery. We've received a transmission from four lightyears away and things aren't looking good.
The *Spaceship Titanic* was an interstellar passenger liner launched a month ago. With almost 13,000 passengers on board, the vessel set out on its maiden voyage transporting emigrants from our solar system to three newly habitable exoplanets orbiting nearby stars.
While rounding Alpha Centauri en route to its first destination—the torrid 55 Cancri E—the unwary *Spaceship Titanic* collided with a spacetime anomaly hidden within a dust cloud. Sadly, it met a similar fate as its namesake from 1000 years before. Though the ship stayed intact, almost half of the passengers were transported to an alternate dimension!
To help rescue crews and retrieve the lost passengers, you are challenged to predict which passengers were transported by the anomaly using records recovered from the spaceship’s damaged computer system.
Help save them and change history!
> ####💡 Getting Started Notebook
> To get started quickly, feel free to take advantage of [this starter notebook](https://www.kaggle.com/code/gusthema/spaceship-titanic-with-tfdf/notebook).
**If you want to talk with other users about this competition, come join our Discord! We've got channels for competitions, job postings and career discussions, resources, and socializing with your fellow data scientists. Follow the link here:** https://discord.gg/kaggle
### Acknowledgments
Photos by Joel Filipe, Richard Gatley and ActionVance on Unsplash.