This repository contains the material for the labs associated with the EPFL master course EE-558 A Network Tour of Data Science (moodle), taught in autumn 2017. Compared to the 2016 edition, the course has been refocused on graph and network sciences. The course material revolves around the following topics:
As such, you get the following material:
- Practical informations
- Installation instructions
- Introduction to Python for Data Science
- Network properties: demo, assignment, solution
- Network models: demo, assignment, solution
- Spectral graph theory: demo, assignment, solution
- Graph signal processing: demo, assignment, solution
- Machine learning: demo, assignment, solution
As a Data Science course, the above activities are realized on real networks, e.g. a social network from Twitter, that students have to collect and clean themselves.
For these labs we'll need git, Python, and packages from the Python scientific stack. If you don't know how to install those on your platform, we recommend to install Anaconda, a distribution of the conda package and environment manager. Please follow the below instructions to install it.
- Open https://www.anaconda.com/download and download the Python 3.x installer for Windows, macOS, or Linux.
- Install with default options.
- Open the Anaconda Prompt (e.g. from the Windows Start menu).
- Execute
conda config --add channels conda-forgeto add the conda-forge channel. It provides many additional packages to conda. - Install git with
conda install git. - Download this repository by executing
git clone https://github.com/mdeff/ntds_2017. - Open the Anaconda Navigator (e.g. from the Windows Start menu).
- From there you can start e.g. Jupyter or Spyder.