- Building machine learning models and neural networks with libraries like Scikit-Learn, PyTorch, or Tensorflow and Keras (now a part of Tensorflow) has become quite easy. Nevertheless, every Data Scientist should at least once build a small neural network from scratch and dive into the calculus of backpropagation. Here you can find a Jupyter-Notebook doing exactly this (MyBinder**).
- Predator Prey model in Python (Jupyter Notebook), stability analysis and numerical solution. Azure Notebooks* | MyBinder**
- Network plotting exercise: https://figshare.com/articles/geneva18/5858109
- Implementation of the geometric multiplex model. It generates synthetic multiplexes with geometric correlations. Paper: Nature Physics 12, 1076–1081 (2016). The program is available here (thanks to Saeed Osat).
- Materials for: Metric clusters in evolutionary games on scale-free networks,
Nature Communications 8, Article number: 1888 (2017)
Data and network model implementation: https://figshare.com/articles/DataAndModel_zip/4817947
- Materials for: Hidden geometric correlations in real multiplex networks, Nature Physics 12, 1076–1081
Supplementary Datasets (hyperbolic maps): https://drive.google.com/file/d/0B_LB9wOzngSba2JSWEFEMDBZalU/view
*Azure requires microsoft/hotmail/skype account, to run the notebook you have to click on “clone”
**MyBinder (beta): allows you to run the notebook remotely without any login.