This app shows a use case using the TIM Forecasting SSE. The use case features a bicycle sharing dataset from Kaggle and shows how to use the SSE to forecast the amount of users of the bicycle sharing service. Apart from the actual forecast, the SSE also gives insight into the model used for forecasting. It shows the importance of the included variables, as well as which transformations and interactions are used in calculating the forecast.
Anyone who's interested in following along to this example, or looking at it in more detail, can do so starting at this link.