In this chapter, we will consider what we've learned in previous chapters to solve a marketing problem. We'll be using some classification and regression techniques to optimize our spending on an ad campaign. On top of this, we'll build upon the previous chapter so that we can improve our models over time. Besides just using a simplistic measure of model quality, we'll dig in and automate some more metrics to control what we can push to production. The challenge that we'll be solving in this chapter will use something referred to as uplift modeling.

Here's the idea, let's say you want to launch a new mailing campaign to generate more business for yourself. Sending each letter costs a small amount of money so ideally, you'd like to only send this marketing campaign to the people who you have a reasonable chance of making money from (known as persuadables). On top of this, there are some people who will stop using your service if you contact them (known...