Notebook Tutorials for Deep Learning in Astronomy
This repository contains tutorials with examples on how to use MiraPy for Deep Learning in Astronomy. We look forward to seeing your contributions to the MiraPy organisation.
Following are the tutorials on using MiraPy:
- Astronomical Image Reconstruction using Autoencoder (Dataset)
- Classification of variable stars in ATLAS catalog (FCN) (Source)
- OGLE Catalog of Variable Stars - Classification of Light curves (RNN) (Source)
- X-Ray Binary Classification (Dataset)
- HTRU1 Pulsar Dataset Image Classification using Convolutional Neural Network (Dataset)
- Playing with Sunspotter Dataset (Dataset)
Notebooks for the following will be added soon:
- Classification of different states of GRS1905+105 X-Ray Binaries using Recurrent Neural Network (RNN)
This repository will updated with more Jupyter notebooks soon. You can find the main repository of MiraPy package here.