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Covers the basics of tensors, including their definition, properties, and decomposition, starting with a motivating example involving Gaussian distributions.
Explores the process of evaluating integrals in multiple dimensions through building two-dimensional integrals from one-dimensional ones and showcasing the flexibility in integration order.
Explores the power method and its applications in topic models and document analysis, emphasizing iterative processes and probability distribution reconstruction.
Covers the manipulation of indicial notation and tensor components, focusing on concepts such as indical notation, free indices, contraction, and the dot product.
