Strategies for Global Deep Learning Forecasting Models

All through the last few chapters, we have been building up deep learning for time series forecasting. We started with the basics of deep learning, saw the different building blocks, practically used some of those building blocks to generate forecasts on a sample household, and finally, talked about attention and transformers. Now, let’s slightly alter our trajectory and take a look at global models for deep learning. In Chapter 10, Global Forecasting Models, we saw why global models make sense and also saw how we can use such a model in the machine learning context. We even got good results in our experiments. In this chapter, we will look at how we can apply similar concepts, but from a deep learning context. We will look at different strategies that we can use to make global deep learning models work better.

In this chapter, we will be covering these main topics:

• Creating global deep learning forecasting models...