Hello :) Today is Day 92!
A quick summary of today:
- got access to the lectures + assignments of XCS224W: ML with Graphs on Stanford’s platform, and covered Lecture 0: Intro to ML with Graphs, and
- Lecture 1.1: Traditional ML on Graphs
Similar lectures may be found on youtube.
Learned about graphs and their application, nodes, edges, adjacency matrices, different types of graphs (undirected, directed, weighted, unweighted), features that help predict nodes, links between nodes and entire graphs, graphlets, clustering coefficients, way more in the notes below ^^
Lecture 0: Intro to ML with Graphs
Lecture 1.1: Traditional methods for ML on Graphs
The rest of lecture 1 covers: 1.2 Node Embeddings and 1.3 Link Analysis: PageRank, Random Walks, and Embeddings
After which I am supposed to do Assignment 1. Exciting stuff in the next days/weeks!
That is all for today!
See you tomorrow :)