Understanding how and why we are here is one of the fundamental questions for the human race. Part of the answer to this question lies in the origins of galaxies, such as our own Milky Way. Yet questions remain about how the Milky Way (or any of the other ~100 billion galaxies in our Universe) was formed and has evolved. Galaxies come in all shapes, sizes and colors: from beautiful spirals to huge ellipticals. Understanding the distribution, location and types of galaxies as a function of shape, size, and color are critical pieces for solving this puzzle.
![Galaxy](http://upload.wikimedia.org/wikipedia/commons/7/74/Ngc5194.jpg)
The Whirlpool Galaxy (M51). Credit: NASA and European Space Agency
With each passing day telescopes around and above the Earth capture more and more images of distant galaxies. As better and bigger telescopes continue to collect these images, the datasets begin to explode in size. In order to better understand how the different shapes (or
morphologies
) of galaxies relate to the physics that create them, such images need to be sorted and classified. Kaggle has teamed up with
[Galaxy Zoo](http://www.galaxyzoo.org/)
and
[Winton Capital](https://www.wintoncapital.com/)
to produce the
Galaxy Challenge,
where participants will help classify galaxies into categories.
![Main Image](https://storage.googleapis.com/kaggle-media/competitions/kaggle/3175/media/mainimage.jpg)
Image Credit: ESA/Hubble & NASA
Galaxies in this set have already been classified once through the help of hundreds of thousands of volunteers, who collectively classified the shapes of these images by eye in a successful
[citizen science](http://www.galaxyzoo.org/#/classify)
crowdsourcing project. However, this approach becomes less feasible as data sets grow to contain of hundreds of millions (or even billions) of galaxies. That's where you come in.
This competition asks you to analyze the JPG images of galaxies to find automated metrics that reproduce the probability distributions derived from human classifications. For each galaxy, determine the probability that it belongs in a particular class. Can you write an algorithm that behaves as well as the crowd does?
Contributors: D. Harvey, C. Lintott, T. Kitching, P. Marshall, K. Willett, Galaxy Zoo
Acknowledgments
The Contributors and the rest of the Galaxy Zoo and Kaggle teams would like to say a big thank you to Winton Capital for helping make this happen. Without their support, we would have not been able to make this competition go ahead.