This is part four in a series on graph theory and graph convolutional networks. If you’ve been reading this whole series, you’ve been with me on this entire journey — through discussing what graph theory is and why it matters, what a graph convolutional network even is and how they work, and now we’re here, to the fun part — building our own GCN. If … [Read more...] about Graph Convolutional Network Implementation With the PROTEINS Benchmark Dataset
What Makes Graph Convolutional Networks Work?
This is the third part of a series on graphs and graph theory in machine learning. By now, if you’ve been following this series, you may have learned a bit about graph theory, why we care about graph structured data in data science, and what the heck a “Graph Convolutional Network” is. Now, I’d like to briefly introduce you to what makes these things work. For my … [Read more...] about What Makes Graph Convolutional Networks Work?
Graph Convolutional Networks — Explained
In my last article on graph theory, I briefly introduced my latest topic of interest: Graph Convolutional Networks. If you’re here thinking “what do those words mean?”, you’re in the right place. In this article, we’re going to break this topic down, step by step. Part I: What’s This Graph Thing? If this is the first you’re hearing this ‘graph’ word, I’m sorry, but you … [Read more...] about Graph Convolutional Networks — Explained
Why Graph Theory Is Cooler Than You Thought
What are Graphs? Talk to a scientist in just about any discipline, and ask them the question — based on their discipline — “how does that stuff work?” You’ll likely find that there are systems and networks that you have to consider before you can really understand how any given thing works: whether that’s the human body, a food chain in an ecosystem, a … [Read more...] about Why Graph Theory Is Cooler Than You Thought