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  • Long Short-Term Memory Neural Networks - MATLAB Simulink
    Long Short-Term Memory Neural Networks This topic explains how to work with sequence and time series data for classification and regression tasks using long short-term memory (LSTM) neural networks For an example showing how to classify sequence data using an LSTM neural network, see Sequence Classification Using Deep Learning
  • Sequence-to-Sequence Regression Using Deep Learning - MATLAB . . .
    This example shows how to predict the remaining useful life (RUL) of engines by using deep learning To train a deep neural network to predict numeric values from time series or sequence data, you can use a long short-term memory (LSTM) network This example uses the Turbofan Engine Degradation Simulation Data Set as described in [1]
  • LSTM and Bidirectional LSTM for Regression Tasks - GitHub
    LSTM is helpful for pattern recognition, especially where the order of input is the main factor We will see in the provided an example how to use Keras [2] to build up an LSTM to solve a regression problem LSTM for regression in Machine Learning is typically a time series problem
  • Building an LSTM Regression Model with Sliding Windows
    How can I efficiently implement the sliding window for inputs and outputs in MATLAB? What is the best way to prepare XTrain, YTrain, XTest, and YTest in a cell array format that MATLAB's LSTM accepts? Any tips on how to structure the LSTM for this kind of regression task?
  • Get Started with Time Series Forecasting - MATLAB Simulink
    This example shows how to create a simple long short-term memory (LSTM) network to forecast time series data using the Deep Network Designer app
  • Simple LSTM prediction example - File Exchange - MATLAB Central
    This example shows the implementation of an LSTM layer used to predict the following samples of a signal based on the first few samples





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