The goal of Quantum Machine Learning is to apply quantum information processing to pattern recognition tasks in machine learning such as classification, regression and clustering. Although still in a premature state, the underlying question whether quantum computation can help to efficiently solve hard machine learning problems attracts growing amounts of interest. Quantum machine learning is thereby closely related to other fields such as quantum optimisation, quantum complexity and quantum probability theory.
The South African Quantum Machine Learning Meetings provide a platform to discuss, share, and present new ideas in the emerging field of quantum machine learning. Set in the stunning South African landscape, both the 2016 Workshop and the 2017 Summer School aim at creating an intimate and productive atmosphere to explore potential and challenges of combining quantum information with data science. A further goal of the Quantum Machine Learning Meetings is to lay the foundation for a joint monograph on Quantum Machine Learning to which all participants are invited to contribute.