Summary
In this chapter, we provided a high-level overview of some emerging graph machine learning algorithms and their applications for new domains. At the beginning of the chapter, we described, using the example provided in Chapter 9, Graph Analysis for Credit Card Transactions, some sampling and augmentation algorithms for graph data. We provided some Python libraries that can be used to deal with graph sampling and graph data augmentation tasks.
We continued by providing a general description of topological data analysis and how this technique has recently been used in different domains.
Finally, we provided several descriptions of new application domains, such as neuroscience, chemistry, and biology. We also described how machine learning algorithms can also be used to solve other tasks, such as image classification, shape analysis, and recommendation systems.
This is it! In this book, we provided an overview of the most important graph machine learning techniques...
