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ntds_2017 - Material for the EPFL master course "A Network Tour of Data Science", edition 2017.

  •    Jupyter

Theoretical knowledge is taught during lectures. Practical knowledge is taught through tutorials. Both are practiced and evaluated through four assignments and a semester project. Below is the teaching material you'll find in this repository.

ntds_2018 - Material for the EPFL master course "A Network Tour of Data Science", edition 2018.

  •    Jupyter

Theoretical knowledge is taught during lectures. Practical knowledge is taught through tutorials. Both are practiced and evaluated through a semester project. More information about the course is found in those slides. Below is the teaching material you'll find in this repository.




AMLSim - This project is intended to provide a multi-agent-based simulator to simulate a set of suspicious activities that relate to money laundering

  •    Python

Important: Please use the "master" branch for the practical use and testing. Other branches such as "new-schema" are outdated and unstable. Wiki pages are still under construction and some of them do not catch up with the latest implementations. Please refer this README.md instead. This project aims at building a multi-agent simulator of anti-money laundering - namely AML, and sharing synthetically generated data so that researchers can design and implement their new algorithms over the unified data.