Challenges and opportunities in quantum machine learning

At the intersection of machine learning and quantum computing, quantum machine learning has recently received considerable attention due to its promise to accelerating data analysis, especially for quantum data, with applications for quantum materials, biochemistry and high-energy physics. Nevertheless, one must tread the hype lightly as many challenges remain to make practical use of quantum learning models. Here we review current methods and applications for quantum machine learning, with a focus on quantum neural networks and quantum deep learning. Finally, we aim to engage in an honest discussion about the opportunities for a quantum advantage with quantum machine learning.