So far, we've used TensorFlow mostly for image processing, and, to a lesser extent, for text sequence processing. In this chapter, we will tackle a specific type of tabular data: time-series, data.
The time series data comes from many domains with usually one commonality—the only field changing constantly is a time or sequence field. It is common in a variety of fields, but especially common in economics, finance, health, medicine, environmental engineering, and control engineering. We'll dive into examples throughout the chapter, but the key thing to remember is that order matters. Unlike in previous chapters, where we shuffled our data freely, time series data cannot be shuffled that way without losing meaning. An added complexity can be the availability of data itself; if we have data available up until the current time with...
