Covers the basics of tensors, including their definition, properties, and decomposition, starting with a motivating example involving Gaussian distributions.
Covers the manipulation of indicial notation and tensor components, focusing on concepts such as indical notation, free indices, contraction, and the dot product.
Explains covariance and contravariance of vectors in multilinear algebra and tensor analysis, focusing on their behavior under changes in basis and scale.
