Selecting the tools
Now that we have a high-level design in mind and we have written down some clear technical requirements, we can begin to select the toolset we will use to implement our solution.
One of the most important considerations on this front will be what framework we use for modeling our data and building our forecasting functionality. Given that the problem is a time series modeling problem with a need for fast retraining and prediction, we can consider the pros and cons of a few options that may fit the bill before proceeding.
The results of this exercise are shown in Figure 7.3:
Figure 7.3 – The considered pros and cons of some different ML toolkits for solving this forecasting problem
Based on the information in Figure 7.3, it looks like the Prophet library would be a good choice and offer a nice balance between predictive power, desired time series capabilities, and experience among the developers and scientists on the team.
