Exploring general techniques to realize and improve supervised deep learning based solutions

Notice that earlier in the chapter we focused on use cases based on problem types and not the problems themselves. Solutions in turn solve and take care of the problem. DL and ML in general are great solvers of issues related to staffing difficulties and for the automation of mundane tasks. Furthermore, ML models in computers can process data much quicker than an average human can, allowing a much quicker response time and much more efficient scaling of any process. In many cases, ML models can help to increase the accuracy and efficiency of processes. Sometimes, they improve current processes, and other times, they make previously unachievable processes possible. However, a single DL model may or may not be enough to solve the problem. Let’s take an example of a solution that can be solved sufficiently with a single DL model.

Consider the use case of using a DL model to predict the...