Regression forecasting and predicting - Practical Machine Learning Tutorial with Python p.5

In this video, make sure you define the X's like so. I flipped the last two lines by mistake: X = np.array(df.drop(['label'],1)) X = preprocessing.scale(X) X_lately = X[-forecast_out:] X = X[:-forecast_out:] To forecast out, we need some data. We decided that we're forecasting out 10% of the data, thus we will want to, or at least *can* generate forecasts for each of the final 10% of the dataset. So when can we do this? When would we identify that data? We could call it now, but consi

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