LSTM (Long short-term memory) is a type of recurrent neural network (RNN) used in deep learning to process and predict sequences of data. The LSTM was designed to address the problem of gradient fading in traditional recurrent neural networks, which occurs when error is backpropagated through multiple layers and important information is lost in the process. The LSTM uses a gated cell structure that allows the network to control the amount of information that is stored and forgotten at each time step, making it particularly suitable for processing long-term sequences of data. LSTMs have been successfully used in a wide variety of deep learning applications, such as natural language processing, speech recognition, text generation and time series prediction.
There is a consensus among executives of the world's leading companies about the crucial impact that Artificial Intelligence (AI) will have on the [...]
Read More »More and more companies are taking advantage of the relevant information they extract from the data they possess and generate to improve their processes and discover new ways to [...]
Read More »The financial sector is constantly implementing new technologies to modernize and digitize its functions. One of the reasons for this is the processing of [...]
Read More »We often wonder what examples of AI we can find in our environment, and the fact is that artificial intelligence is a concept that in English has [...]
Read More »
