The problem Exoplanet Hunting using Machine Learning solves

Exoplanets are planets beyond our own solar system. Thousands have been discovered in the past two decades, mostly with NASA’s Kepler Space Telescope.

Kepler was very sensitive to changes in flux (light intensity). Periodically, data was beamed down to Earth and after a bit of de-noising, they were open-sourced via the Mikulski Archive.

We may have imagined life on other planets in books and film for centuries, but detecting actual exoplanets is a recent phenomenon. Planets on their own emit very little if any light. We can only see Jupiter or Venus in the night sky because they reflect the sun’s light. If we were to look at an exoplanet (the nearest one is over 4 light-years away), it would be very close to a brilliantly lit star, making the planet impossible to see.

Therefore, with the help of this project, we can detect the explanets and see if they are in the habitable zone or not.
This search could result in discovery of worlds similar to our planet which have the essential conditions to support life or it could help us realize the irreplaceable nature of our planet and hence the need to conserve its resources.