Recurrent Neural Networks (RNNs) belong to the Artificial Intelligence category and also play an important role in Big Data and Smart Data, as well as in automation. RNNs are special forms of artificial neural networks that have been developed to handle data that has a sequence \u2013 for example, in texts, sound, or time series.<\/p>\n
Unlike classic artificial neural networks, RNNs can \u201cremember\u201d information from previous steps and use it for later decisions. This allows them to recognise connections that are not immediately obvious. This makes RNNs particularly useful for tasks such as speech and text recognition, translations, or even predicting stock prices.<\/p>\n
A striking example: when typing in a smartphone message, the device often suggests how an unfinished sentence could continue. Behind this often lies a recurrent neural network that has learned patterns from previous text inputs and suggests the next words based on them.<\/p>\n
This helps RNNs to automate everyday processes for companies, make services smarter, and contribute to the meaningful evaluation of large amounts of data.<\/p>","protected":false},"excerpt":{"rendered":"