Conversion of notebooks of ML4Nets course

[IngoScholtes]

To test whether the functionality needed for the ML4Nets course has been implemented in pathpyG, we should start converting the practice notebooks, which are available here.

• Week 01: Introduction to python and pathpyG [@IngoScholtes]
• Week 02: Shortest paths, Components, Spectral Clustering [@IngoScholtes]
• Week 03: Random Graphs and Molloy-Reed Model [@IngoScholtes]
• Week 04: Stochastic Block Model [@chrisbloecker]
• Week 05: Entropy and Huffman Coding [@chrisbloecker]
• Week 06: Random Walks and InfoMap [@FranziskHeeg]
• Week 07: Similarity Scores and Link Prediction [@IngoScholtes]
• Week 08: Dimensionality Reduction and Laplacian Eigenmaps [@VincenzoPerri]
• Week 09: Logistic Regression and Neural Networks [does not use pathpyG]
• Week 10: DeepWalk and node2vec [@lisiq]
• Week 11: Graph Neural Networks [@lisiq]

[lisiq]

Week 11 done