The final level of our hierarchy is the one where we, as the engineer, have the least direct control over the training process, but where we also potentially get a good answer for very little effort!
The development time that's required to search through many hyperparameters and algorithms for your problem can be large, even when you code up reasonable-looking search parameters and loops.
Given this, the past few years have seen the deployment of several
AutoML libraries and tools in a variety of languages and software ecosystems. The hype surrounding these techniques has meant they have had a lot of airtime, which has led to several data scientists questioning when their jobs will be automated away. As we mentioned previously in this chapter, in my opinion, declaring the death of data science is extremely premature and also dangerous from an organizational and business performance standpoint. These tools have been given such a pseudo-mythical status that many companies could...