Data Science, Machine Learning, Time Series Forecasting, Lstm, Deep Learning.
epochs=500, batch_size=18, verbose=2) # Make predictions lstm_predictions = model.predict(X_test) lstm_fitted = model.predict(X_train) forecasts = [np.diag(np.fliplr(lstm_predictions), i).mean() for i in range(0, -lstm_predictions.shape[0], -1)] fits = [np.diag(np.fliplr(lstm_fitted), i).mean() for