Forecasting, Deep Learning, Arima, Goldman Sachs, Data Science.
the prediction output = model_fit.forecast() yhat = output[0] return yhat # Split data into train and test sets X = dataset_ex_df.values size = int(len(X) * 0.8) train, test = X[0:size], X[size:len(X)] # Walk-forward validation history = [x for x in train] predictions = list() for t in