This repository contains practical assignments on network analysis. All assignments are presented as Jupyter notebooks, that can be done by writing code instead of the line
# YOUR CODE HERE
All notebooks contain test cells with assert statements that help you understand whether your code is correct.
Topics:
- Introduction to Network Science
- Power Law and Scale-free Networks
- Random Networks
- Generative Network Models
- Centrality Measures
- Links Analysis and Structure
- Community Detection
- Community Detection, part 2
- Compartmental Epidemic Models
- Epidemics on Graphs
- Node Classification
- Link Prediction
- Node Embedding
- Graph Neural Networks
- Influence Propagation
- Knowledge Graph Embedding
- Multihop Reasoning in Knowledge Graphs
Here are also descriptions of some competitions held among students to solve practical tasks on graphs:
Lecture materials: http://leonidzhukov.net/hse/2021/networkscience/
Youtube channel with records of lectures: https://youtube.com/playlist?list=PLriUvS7IljvkGesFRuYjqRz4lKgodJgh2