Introduction Recurrent Neural Networks (RNNs) are a specific type of Neural Networks (NNs) that are especially relevant for sequential data like time series, text, or audio data. Traditional neural networks process each input independently, meaning they cannot retain information about previous inputs. This makes them ineffective for tasks that require understanding sequences, such as time series forecasting or natural language processing. RNNs however, process the data sequentially, which enables them to remember data from the past.