Key research areas in quantum machine learning include modeling purely classical data on quantum computers, developing quantum-inspired classical algorithms, and performing supervised learning with quantum classifiers. Additional areas of focus involve adaptive layer-wise learning for quantum neural networks, quantum dynamics learning, generative modeling of mixed quantum states, and classification using quantum neural networks on near-term processors.