Considerations for selecting technologies

This chapter has introduced four classes of NLU technologies:

• Rule-based
• Statistical machine learning
• Deep learning and neural networks
• Pre-trained models

How should we decide which technology or technologies should be employed to solve a specific problem? The considerations are largely practical and have to do with the costs and effort required to create a working solution. Let’s look at the characteristics of each approach.

Table 3.3 lists the four approaches to NLU that we’ve reviewed in this chapter and how they compare with respect to developer expertise, the amount of data required, the training time, accuracy, and cost. As Table 3.3 shows, every approach has advantages and disadvantages. For small or simple problems that don’t require large amounts of data, the rule-based, deep learning, or pre-trained approaches should be strongly considered, at least for part of the pipeline. While...