Chapter 10. Example: digital display advertising
This chapter covers
- Visualizing and preparing a real-world dataset
- Building a predictive model of the probability that users will click a digital display advertisement
- Comparing the performance of several algorithms in both training and prediction phases
- Scaling by dimension reduction and parallel processing
Chapter 9 presented techniques that enable you to scale your machine-learning workflow. In this chapter, you’ll apply those techniques to a large-scale real-world problem: optimizing an online advertising campaign. We begin with a short introduction to the complex world of online advertising, the data that drives it, and some of the ways it’s used by advertisers to maximize return on ...
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