– Dr. Deepti Sidhaye
Do you wish to learn machine learning? Do you wish to be a student at Stanford? Do you think that both these wishes will remain unfulfilled because you are not able to physically go to Stanford? Well, not anymore. The reason being that Stanford will be offering an online free Machine Learning with Graphs course from the fall of 2022! This particular course (Stanford CS224W) will focus on computational, algorithmic, and modeling challenges specific to the analysis of massive graphs. All you need to do is be well-versed with the pre-requisites. And what are these pre-requisites? For starters, one needs to have knowledge of basic computer science principles which will be sufficient to write a reasonably non-trivial computer program (Recommendation: Stanford courses such as CS107 or CS145 or equivalent). One also needs to be familiar with the basic probability theory (Recommendation: Stanford courses such as CS109 or Stat116). And as one would expect, one has to be familiar with basic linear algebra. Overview of the expected background will be given in the recitation sessions in the first few weeks of the course. The topics such as Representation learning and Graph Neural Networks, algorithms for the World Wide Web, reasoning over Knowledge Graphs, influence maximization, disease outbreak detection, and social network analysis will be covered in the course. The relevance of this course comes from the fact that a graph of relationships between objects can represent complex data. Hence, such networks can be a useful tool for modeling social, technological, and biological systems. In this course, machine learning techniques and data mining tools required to understand such networks will be introduced to the students via the study of underlying graph structure and its features.