Backpropagation through time

Backpropagation through time, or BPTT, is a way of training a computer model to remember patterns in data. This helps the model make better decisions in the future. It works by going back in time and analyzing past data to look for patterns that have worked in the past. Then, it applies those patterns to new data. This helps the model to learn as it goes, so that it can make better predictions in the future.