Summary

We have come to the end of our journey through the world of time series forecasting. In the last couple of chapters, we addressed a few mechanics of forecasting, such as how to do multi-step forecasting, and how to evaluate forecasts. Different validation strategies for evaluating forecasts and forecasting models were the topics of the current chapter. We started by enlightening you as to why model validation is an important task. Then, we looked at a few different validation strategies, such as the holdout strategies, and navigated the controversial use of cross-validation for time series. We spent some time summarizing and laying down a few guidelines to be used to select a validation strategy. To top it all off, we looked at how these validation strategies are applicable to datasets with multiple time series and talked about how to adapt them to such scenarios.

With that, we have come to the end of the book. Congratulations on making it all the way through, and I hope...