This tutorial introduces the foundations of machine learning for nanoindentation and nanomechanical data analysis. The session covers the basic concepts of supervised and unsupervised learning, feature extraction from indentation curves, clustering and classification of indentation datasets, analysis of high-throughput nanoindentation maps, and advanced workflows based on the full load-displacement curve. It discusses how data-driven methods can support phase identification, detection of anomalous curves, interpretation of mechanical populations, and integration with correlative microstructural information.
Tutorial Slides
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