Cross-identification of radio objects and host galaxies by applying machine learning on crowdsourced training labels.
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docs Fixed Norris imports #221 Feb 20, 2017
examples Updated Yan method to OOP Sep 13, 2016
tex Idea of how to have interactive clicking of scatter plot to show image May 15, 2017
.gitattributes linguist-ignored TeX Sep 16, 2016
.gitignore Re-added crowdastro.json Aug 31, 2016
.travis.yml Still trying to fix numba on travis. Sep 13, 2016
README.rst Fixed PyPI badge Aug 31, 2016
license.txt Added MIT license May 4, 2016
mkdocs.yml Updated data sources to use the newer dataset, #183 Sep 25, 2016 Merge pull request #20 from MatthewJA/mongo-load-fix Mar 9, 2016
requirements-docs.txt Added a requirements file for RTD Sep 14, 2016
requirements.txt Updated requirements to have numba Sep 13, 2016 Minor update Sep 21, 2016
setup.cfg Added CLI. Refactored compile CNN to work with CLI. Aug 31, 2016



This project aims to develop a machine learned method for cross-identifying radio objects and their host galaxies, using crowdsourced labels from the Radio Galaxy Zoo.

PyPI Travis-CI Documentation Status DOI

For setup details, see the documentation on Read the Docs.

For a brief description of each notebook, see the documentation here.

The cross-identification dataset is available on Zenodo.