Introduction
Time series data is basically a sequence of measurements that are collected over time. These measurements are taken with respect to a predetermined variable and at regular time intervals. One of the main characteristics of time series data is that the ordering matters!
The list of observations that we collect is ordered on a timeline, and the order in which they appear says a lot about underlying patterns. If you change the order, this would totally change the meaning of the data. Sequential data is a generalized notion that encompasses any data that comes in a sequential form, including time series data.
Our objective here is to build a model that describes the pattern of the time series or any sequence in general. Such models are used to describe important features of the time series pattern. We can use these models to explain how the past might affect the future. We can also use them to see how two datasets can be correlated, to forecast future values, or to control a given...
