We’ve already leveraged RNNs for NLP. In this chapter, we create experiments to forecast with time series data. We use the famous Weather dataset to demonstrate both a univariate and a multivariate example.
A RNN is well suited for time series forecasting because it remembers the past and its decisions are influenced by what it has learned from the past. So it makes good decisions as data changes. Time series forecasting is deploying a model to predict future values based on previously observed values.
Time series data is different than what we’ve worked with so far because ...
