Further reading
To learn more about the topics that were covered in this chapter, take a look at the following resources:
- Stamile, C., Marzullo, A., and Deusebio, E. (2021). Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms. Packt Publishing.
- Liiv, I. (2021). Data Science Techniques for Cryptocurrency Blockchains. Springer.
- Spindl. (n.d.). Introduction: https://docs.spindl.xyz/spindl/overview/introduction.
- Regarding GraphSAGE:
- Ruberts, A. (2021, May 4). GraphSAGE for Classification in Python. Well Enough: https://antonsruberts.github.io/graph/graphsage/.
- Özçelik, R. (2019, October 25). An Intuitive Explanation of GraphSAGE. Medium: https://towardsdatascience.com/an-intuitive-explanation-of-graphsage-6df9437ee64f.
- Demos:
- StellarGraph basics – StellarGraph 1.2.1 documentation. (n.d.). Welcome to StellarGraph’s documentation! – StellarGraph 1.2.1 documentation: https...
