Summary

In this chapter, we covered some tools and methods to help you gain an understanding of your system and the business problem you are trying to solve. Some of these methods will be new or unfamiliar to even experienced data scientists, but it is important to take the time to internalize them and practice them on your projects. Some of this will feel unnecessary given the time pressures. This is one of the reasons tools such as DataRobot are beneficial, as they reduce the time you need to spend on repetitive tasks and allow you to focus on things that tools cannot do.

Hopefully, I have convinced you that the combination of data science teams focusing more on understanding the problem and using automation tools for some of the model building and tuning tasks provides the best value to an organization. A lot of the work done here will also come in handy toward the end of the project when we are getting ready to operationalize the models into the organization. Specifically, in...