Lectures related to Data Representations: Learning Methods

Covers the basics of Scanning Electron Microscopy, including setup, signals, and challenges like beam damage and charging.

Presents solutions to exercises on Canonical Correlation Analysis, exploring correlation, Gram matrices, kernel matrices, and vector properties.

Covers the concept of gradient descent, a universal algorithm used to find the minimum of a function.