This repository contains the source code for the mlrose Python package. This package implements a range of Machine Learning, Randomized Optimization and SEarch algorithms, to allow users to explore the properties of these algorithms under various conditions.

mlrose was written in Python 3 and requires NumPy, SciPy and Scikit-Learn (sklearn).

The latest released version is available at the Python package index < insert link to PyPi page> and can be installed using pip:

pip install mlrose

The official mlrose documentation can be found here:

mlrose was written by Genevieve Hayes and is distributed under the 3-Clause BSD license.

You can cite mlrose in research publications and reports as follows:

• Hayes, G. (2018). mlrose: Machine Learning, Randomized Optimization and SEarch package for Python. https://github.com/gkhayes/mlrose. Accessed: day month year.

BibTeX entry:

@misc{Hayes18,
 author = {Hayes, G},
 title 	= {{mlrose: Machine Learning, Randomized Optimization and SEarch package for Python}},
 year 	= 2018,
 howpublished = {\url{https://github.com/gkhayes/mlrose}},
 note 	= {Accessed: day month year}
}