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Building an LSTM model with Keras

Building an LSTM model with Keras - Python Tutorial

From the course: Applied AI for IT Operations (AIOps)

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Building an LSTM model with Keras

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- Now, we will build an LSTM models with Keras to predict a time series. As discussed in the earlier video, to predict each data point, we need to provide a lookback of data points. For this, we need to create a data set that associates each data point with the previous 168 data points, which is a week's worth of lookback. We do so using the Create RNN Dataset function. This function takes as input, a data set and a lookback period. It then creates the feature Vector X, and the prediction Y. X contains the previous 168 data points for the corresponding Y. This means that if we pass four weeks of data, we will only get three weeks of X and Y, since the first week will be lost in the lookback. We iterate over the data set, we create X using the last 168 lookback points and Y being the current point. We return the final array then. We use this method to create X and Y arrays for the training data set. Then we reshape X as a three dimensional array for use with LSTM. Finally, we print…

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