Time Series Forecasting in Python

13 Data windowing and creating baselines for deep learning

This chapter covers

• Creating windows of data
• Implementing baseline models for deep learning

In the last chapter, I introduced deep learning for forecasting by covering the situations where deep learning is ideal and by outlining the three main types of deep learning models: single-step, multi-step, and multi-output. We then proceeded with data exploration and feature engineering to remove useless features and create new features that will help us forecast traffic volume. With that setup done, we are now ready to implement deep learning to forecast our target variable, which is the traffic volume.

In this chapter, we’ll build a reusable class that will create windows of data. This step ...