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Time series prediction by recurrent neural networks | | Learn Neural Networks
Time series forecasting tasks are a complex type of predictive modelling problem. In contrast to regression predictive modelling, time series also add the complexity of the sequence to input variables. A powerful type of neural network designed to process sequences are recurrent neural networks. A network with a long short memory or LSTM network is a type of recurrent neural network used in deep learning. Here we will develop the LSTM neural networks for the standard time series prediction problem. These examples will help you develop your own structured LSTM networks for time series forecasting tasks. The task that we will consider is the problem of forecasting passenger traffic. The task is to predict the number of passengers of international airlines. The data set is available for free from the address ds=22u3&display=line with the file name "international-airlines