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 * [Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) - Book/iPython notebooks on Probabilistic Programming in Python
 * [MLlib in Apache Spark](http://spark.apache.org/docs/latest/mllib-guide.html) - Distributed machine learning library in Spark
 * [scikit-learn](http://scikit-learn.org/) - A Python module for machine learning built on top of SciPy.
+* [astroML](http://www.astroml.org/) - Machine Learning and Data Mining for Astronomy.
 * [graphlab-create](http://graphlab.com/products/create/docs/) - A library with various machine learning models (regression, clustering, recommender systems, graph analytics, etc.) implemented on top of a disk-backed DataFrame.
 * [BigML](https://bigml.com) - A library that contacts external servers.
 * [pattern](https://github.com/clips/pattern) - Web mining module for Python.