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.
5 Big Data challenges can be highlighted which are defined as V (volume, velocity, veracity, variety and value). R. Narasimhan discussed 3V with [...]
Read More »All businesses usually plan for annual growth, although not all of them achieve it. Increasing the sales of a company in 2022 is [...]
Read More »Business opportunities are everywhere and many times we do not know which are the sectors with the greatest potential for entrepreneurship.
Read More »In today's oversaturated information market, it is becoming increasingly difficult to retain users. For companies, competition is increasingly [...]
Read More »
