Summary

In this chapter, we covered how to build and compare models by leveraging DataRobot's capabilities. As you saw, DataRobot makes it very easy to build many models quickly and helps us compare them. As you experienced, we tried many things and built dozens of models. This is DataRobot's key capability, and its importance to a data science team cannot be overstated. If you were to build these models on your own in Python, it would have taken a lot more time and effort. Instead, we used that time and thinking to experiment with different ideas and put more energy toward understanding the problem. We also learned about blueprints that encode best practices. These blueprints can be useful learning tools for new and experienced data scientists alike. We also learned how DataRobot can build ensemble or blended models for us.

It might be tempting to jump ahead and start deploying one of these models, but it is important to not directly jump to that without doing some analysis...