Interactive ML web app classifying stars, galaxies, and quasars from SDSS DR17 photometric data using a Random Forest model, deployed with Streamlit.
Modular toolkit for efficient bulk downloading and management of SDSS spectra and imaging data, starting with a multithreaded downloader.
Estimating the Quasar Formation Rate Using Sloan Digital Sky Survey Data
A project to classify galaxies, using deep learning models trained on astronomical survey datasets.
Creatively visualize local galaxy structure.
CNN for galaxy morphology classification using SDSS images (Galaxy Zoo) with astroNN preprocessing; Keras/TensorFlow notebook with metrics & confusion matrix.
This repository has the code for a python implementation for the Splines'n Lines method from Kent D., Budavári T., Loredo T., and Ruppert D. It also contains some general explorations of Quassar data from the Sloan Digital Sky Survey. ArXiv for Splines'n Lines: https://arxiv.org/abs/2310.19340
Classify galaxy images into spiral, elliptical, or irregular types using a convolutional neural network and the Galaxy10 DECals dataset.
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