In 2007, the Galaxy Zoo project was launched for morphological classification of a large number of galaxies. In this project, 900,000 images were considered for classification that were taken from the Sloan Digital Sky Survey (SDSS) for the past 7 years. The task was to study each picture of a galaxy, classify it as elliptical or spiral, and determine whether it was spinning or not. The team of Astrophysicists led by Kevin Schawinski in Oxford University were in charge of this project and Kevin and his colleague Chris Linlott figured out that it would take a period of 3–5 years for such a team to complete the work. There they came up with the idea of using Machine Learning and Data Science techniques for analyzing the images and classifying them.