Most of the models that we have discussed up to this point predict a property about something based on other properties related to that something. For example, we predicted the species of a flower based on measurements of the flower. We also tried to predict the progression of the disease diabetes in a patient based on medical attributes about that patient.
The premise of time series modeling is different from these types of property prediction problems. Simply put, time series modeling helps us predict the future based on attributes about the past. For example, we may want to predict future stock prices based on previous values of that stock price, or we may want to predict how many users will be on our website at a certain time based on data about how many users were on our website at previous times. This is sometimes called forecasting.
The...
