The basics of manipulating and viewing image data with Julia.
For full course information, visit https://github.com/mitmath/18S191

Contents
0:00 - Introduction
1:12 - What is an Image (to Julia)
5:10 - Indexing and slicing
7:42 - Concatenating images
9:19 - Manipulating pixel data
12:01 - Broadcasting functions
15:07 - Blurring
17:56 - Preview of edge-detection

Contribute to mitmath/18S191 development by creating an account on GitHub.

🎈 Lightweight reactive notebooks for Julia. Contribute to fonsp/Pluto.jl development by creating an account on GitHub.

Introducing a fresh, new notebook system for rapid prototyping! Pluto understands global references between cells, and reactively re-evaluates cells affected by a code change. At JuliaCon, we will show how Pluto can liven up your workflow.

Whether you’re a scientist, a finance professional or an engineer, you use notebooks like Jupyter to tell a story. You fiddle a bit with your code, running cells here and there, and when you’re done - you restart the kernel and keep your fingers crossed that it’ll all work together when you press “run all”.

🙋 In Pluto, things work differently. When you change a variable, Pluto automatically re-runs the cells that refer to it. And when you delete a cell, the variables, methods and imports from the old code disappear. Unlike Jupyter or Matlab, there is no mutable workspace, but rather a one-to-one correspondence between variables and code.

🚨 Reactivity is not just fun for mathematical tricks! It guarantees that the code you see exactly matches the variables you're working…

🎈 Lightweight reactive notebooks for Julia. Contribute to fonsp/Pluto.jl development by creating an account on GitHub.