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Transformations - Composability and Linearity in Computational Thinking - Lecture 4

The Julia Programming Language via YouTube

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Overview

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This lecture explores how linear and nonlinear transformations can be represented and composed in Julia. It uses vector-valued and parameterized functions, perspective maps, and image processing as contexts for programming and mathematical reasoning.

Syllabus

Introduction.
Playing with transformations.
Why Image Processing to learn Julia?.
Last lecture leftovers: Perspective maps, Linear perspective interactive.
Julia style(advanced): Defining vector valued functions.
Functions with parameters.
Linear transformations: a collection.
Nonlinear transformations: a collection.
Composition.
Difference between sin and sin(x).
Definition of Linear Transformations.
To be discussed in next lecture.

Taught by

The Julia Programming Language

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