Quantopo is a quantum machine learning project focused on leveraging the geometry of quantum mechanics within quantum computers to improve on tools in statistical modeling and topological data analysis.

As of today, this repo contains work on Quantopo's first proof-of-concept with a continuous-variable quantum architecture model of integrated photonic circuits (under projects/QGLM/Xanadu) and data-driven quantum circuit learning with Rigetti's quantum backend (under projects/DDQCL/Rigetti). Proprietary algorithms are developed in-house. Our open-sourced quantum algorithms under research and development will be released periodically.

Moreover, proper documentations are coming soon. In the meantime, checkout this Quantum Machine Learning (QML) course to get up to speed on QML: https://courses.edx.org/courses/course-v1:University_of_TorontoX+UTQML101x+1T2019/course/. The GitLab account associated with the course can be found at: https://gitlab.com/qosf/qml-mooc

-Check out the new content under ml_docs/watson_ibm. Bringing new materials for learning the Data Science pipeline on Watson Studio. ;)

-New content under api/examples/kaggle_learning. API development for getting Data Science into production! A three-part rollout!