Machine learning: Basics of data-driven materials modeling

This lecture covers the basics of data-driven materials modeling, focusing on dimensionality reduction and linear regression. Topics include machine learning concepts, model training, testing, and generalization error analysis. The instructor explains the importance of inputs, samples, targets, models, and loss functions in the context of materials science.