Data access and visualization for MaNGA. http://sdss-marvin.readthedocs.io/en/latest/

Materials for SDSS 2019, Bellevue WA

Estimating galaxy gas mass fractions using SDSS imaging

Using SDSS imaging to predict galaxy metallicity. Maintained by @jwuphysics @boada

Risk Changes SDSS development page

Retrieve and analysis data from SDSS (Sloan Digital Sky Survey)

The SDSS Python template and coding standards.

SDSS observer graphical interface

The Illustris Virtual Observatory is an expanded iteration of the Sunpy module(ptorrey) for creating synthetic SDSS, HST, or JWST images of galaxies from the Illustris simulation. For instructions on how to install/use this program, please go to this address:

The Brain™ of Marvin.

Curve fitting routines for astrophysical (SDSS) spectrographs

A tutorial on classification and photometric redshift regression of astronomical sources using supervised machine learning techniques.

TensorFlow implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.

Using machine learning to predict the mass of quasar supermassive black holes

This repository contains the code and data for the Astronomical Object Classification Project. The project focuses on classifying celestial objects (stars, galaxies, and quasars) based on their spectral characteristics using data from the Sloan Digital Sky Survey (SDSS).

Repo for a Data analysis project to find Distances, Luminosities, Fluxes, Star Formation Rates, and WISE image processing for galaxies in the MaNGA survey.

A selection of workbooks to analsyse SDSS data

Product for managing the SDSS environment tree

GaMorNet is a CNN based on AlexNet to classify galaxies morphologically

This project is a full machine learning pipeline for Star/Galaxy classification using the SDSS dataset. It also contains a detailed report on the development and a DockerFile to easily replicate the results.