Basics of Graphs
Explore the basics of graphs and graph neural networks by understanding how data structure and features separate to form powerful models. Learn about adjacency matrices, node features, and real-world applications such as images, social networks, and molecular data.
We'll cover the following...
We'll cover the following...
In this lesson, we will explore graph neural networks and graph convolutions. Graphs are a super general representation of data with intrinsic structure.
The most intuitive transition to graphs is by starting from images.
Why?
Because images are highly-structured data. Their components (pixels) are arranged in a meaningful way. If you change the way pixels are structured, the image loses its meaning. ...