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| from sklearn.preprocessing import MinMaxScaler | |
| #create numpy.ndarray | |
| df_arr= df1.values | |
| df1.values = df_arr.astype('float32') | |
| df_arr = np.reshape(df_arr, (-1, 1)) #LTSM requires more input features compared to RNN or DNN | |
| scaler = MinMaxScaler(feature_range=(0, 1))#LTSM is senstive to the scale of features | |
| df_arr = scaler.fit_transform(df_arr) |
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