Python Library for expressing Quantum Machine Learning Algorithms as well as utilzing core Quantum computing functionality to model quantum behavior.
The qLearn package includes lightweight modules for analyzing multi-state proablistic systems, along with the ability to utilize quantum mechanical features such as entanglement and superposition to complement the complexity requirements of many Bayes-like probablistic systems.
The paper in which this approach is developed is titled "A Quantum Approach to Machine Learning" and can be found at: https://s3.amazonaws.com/quantum-approach-machine-learning/A+Quantum+Approach+to+Machine+Learning.pdf This discussion formulates the underlying approach and mathmatics behind the implementation in this Library. It is a useful resource for the user of the library to formulate ideas of new use cases and provide exposure to the power these algorithms may hold.