Quantum Machine Learning: Theory and Practice in Action

Dr. Alexey Melnikov & Dr. Asel Sagingalieva

AI-Director & Head of Quantum Machine Learning @TerraQuantum AG

Abstract

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This talk surveys quantum machine learning from first principles to practice, with a focus on quantum neural networks (QNNs) and hybrid quantum‑classical architectures. Alexey will show how data‑encoding choices govern QNN expressivity via truncated Fourier series and motivate parallel quantum layers that are practical in the NISQ era. Asel will be further outlining an end‑to‑end engineering pipeline that operationalizes and optimizes hybrid QNN models from data to deployment. With our case studies in time series forecasting, image classification, and physics‑informed simulation we will demonstrate competitive accuracy with fewer parameters.