3 Graphs in machine learning applications
This chapter covers
- The role of graphs in the machine learning workflow
- How to store the training data and the resulting model properly
- Graph-based algorithms for machine learning
- Data analysis with graph visualization
In this chapter, we’ll explore in more detail how graphs and machine learning can fit together, helping to deliver better services to end users, data analysts, and businesspeople. Chapters 1 and 2 introduced general concepts in machine learning, such as
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The different phases that compose a generic machine learning project (specifically, the six phases of the CRISP-DM model: business understanding, data understanding, data preparation, modeling, evaluation, and deployment)
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The importance ...
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