Transformations - Composability and Linearity in Computational Thinking - Lecture 4

Transformations - Composability and Linearity in Computational Thinking - Lecture 4

Explore transformations, composability, and linearity in this MIT Computational Thinking Spring 2021 lecture. Dive into image processing as a tool for learning Julia programming, examine perspective maps and linear perspective interactively, and master advanced Julia techniques for defining vector-valued functions. Discover various linear and nonlinear transformations, understand function composition, and grasp the distinction between sin and sin(x). Conclude with a comprehensive definition of linear transformations, setting the stage for future discussions.