This project aims to classify galaxies based on their morphologies using advanced machine learning techniques. In this project, ResNet50 is adapted for feature extraction, and K-means and spectral clustering were utilized to categorize galaxy images into four types: Cigar-shaped, Spiral, and two groups of Elliptical galaxies, one of which exhibited more noise. The analysis demonstrated the effectiveness of these techniques in distinguishing subtle differences in galaxy structures.
