Update joblib import so that new scikit-learn versions can be used (#…

…2546)

v1/python-sdk/tutorials/automl-with-azureml/classification-text-dnn/infer.py

@@ -3,7 +3,7 @@
 import pandas as pd
 import numpy as np
 
-from sklearn.externals import joblib
+import joblib
 
 from azureml.automl.runtime.shared.score import scoring, constants
 from azureml.core import Run, Dataset

v1/python-sdk/tutorials/automl-with-azureml/forecasting-bike-share/forecasting_script.py

@@ -1,6 +1,6 @@
 import argparse
 from azureml.core import Dataset, Run
-from sklearn.externals import joblib
+import joblib
 
 parser = argparse.ArgumentParser()
 parser.add_argument(

v1/python-sdk/tutorials/automl-with-azureml/forecasting-demand-forecasting-many-models/scripts/inference_script_naive.py

@@ -7,7 +7,7 @@
 import os
 import argparse
 from azureml.core import Dataset, Run
-from sklearn.externals import joblib
+import joblib
 from pandas.tseries.frequencies import to_offset
 
 try:

v1/python-sdk/tutorials/automl-with-azureml/forecasting-demand-forecasting-tcn/scripts/inference_script_naive.py

@@ -7,7 +7,7 @@
 import os
 import argparse
 from azureml.core import Dataset, Run
-from sklearn.externals import joblib
+import joblib
 from pandas.tseries.frequencies import to_offset
 
 try:

v1/python-sdk/tutorials/automl-with-azureml/forecasting-demand-forecasting-tcn/scripts/inference_script_tcn.py

@@ -12,7 +12,7 @@
 import pandas as pd
 
 from pandas.tseries.frequencies import to_offset
-from sklearn.externals import joblib
+import joblib
 from sklearn.metrics import mean_absolute_error, mean_squared_error
 
 from azureml.data.dataset_factory import TabularDatasetFactory

v1/python-sdk/tutorials/automl-with-azureml/forecasting-energy-demand/forecasting_script.py

@@ -6,7 +6,7 @@
 
 import argparse
 from azureml.core import Dataset, Run
-from sklearn.externals import joblib
+import joblib
 from pandas.tseries.frequencies import to_offset
 
 parser = argparse.ArgumentParser()

v1/python-sdk/tutorials/automl-with-azureml/forecasting-github-dau/infer.py

@@ -4,7 +4,7 @@
 import numpy as np
 import pandas as pd
 
-from sklearn.externals import joblib
+import joblib
 from sklearn.metrics import mean_absolute_error, mean_squared_error
 
 from azureml.automl.runtime.shared.score import scoring, constants

v1/python-sdk/tutorials/automl-with-azureml/forecasting-orange-juice-sales/forecasting_script.py

@@ -6,7 +6,7 @@
 
 import argparse
 from azureml.core import Dataset, Run
-from sklearn.externals import joblib
+import joblib
 from pandas.tseries.frequencies import to_offset
 
 parser = argparse.ArgumentParser()

v1/python-sdk/tutorials/automl-with-azureml/forecasting-pipelines/scripts/infer.py

@@ -6,7 +6,7 @@
 import pandas as pd
 
 from pandas.tseries.frequencies import to_offset
-from sklearn.externals import joblib
+import joblib
 from sklearn.metrics import mean_absolute_error, mean_squared_error
 
 from azureml.data.dataset_factory import TabularDatasetFactory

v1/python-sdk/tutorials/automl-with-azureml/forecasting-recipes-univariate/forecasting_script.py

@@ -7,7 +7,7 @@
 import argparse
 from azureml.core import Dataset, Run
 from azureml.automl.core.shared.constants import TimeSeriesInternal
-from sklearn.externals import joblib
+import joblib
 
 parser = argparse.ArgumentParser()
 parser.add_argument(