This project implements a neural network to classify galaxies based on types - spiral, elliptical, irregular based on the GalaxyZoo dataset. This is a project I made few months ago. My aim was to verify the results of a research paper I read. (https://academic.oup.com/mnras/article/406/1/342/1073212) The neural network classifies about 667,000 galaxies into 3 categories with an accuracy of 93%, thus, verifying the result of the paper.
The dataset can be downloaded from https://data.galaxyzoo.org/. I've used the .csv format.
Attributes used are: NVOTE P_EL P_CW P_ACW P_EDGE P_DK P_MG P_CS P_EL_DEBIASED P_CS_DEBIASED and SPIRAL ELLIPTICAL UNCERTAIN
The artificial neural network has 2 hidden layers.