What to Do If the System Isn’t Working

In this chapter, we will discuss how to improve systems. If the original model’s first round of training fails to produce a satisfactory performance or the real-world scenario that the system addresses undergoes changes, we need to modify something to enhance the system’s performance. In this chapter, we will discuss techniques such as adding new data and changing the structure of an application, while at the same time ensuring that new data doesn’t degrade the performance of the existing system. Clearly, this is a big topic, and there is a lot of room to explore how to improve the performance of natural language understanding (NLU) systems. It isn’t possible to cover all the possibilities here, but this chapter should give you a good perspective on the most important options and techniques that can improve system performance.

We will cover the following topics in this chapter:

• Figuring out that a...