update names

ignore/doc-qa/how-to-set-up-training-targets/Local.py

@@ -12,9 +12,6 @@ from azureml.core.runconfig import RunConfiguration
 run_local = RunConfiguration()
 
 run_local.environment.python.user_managed_dependencies = True
-
-# Choose a specific Python environment by pointing to a Python path. For example:
-# run_config.environment.python.interpreter_path = '/home/ninghai/miniconda3/envs/sdk2/bin/python'
 #</run_local>
 
 from azureml.core import Workspace

ignore/doc-qa/how-to-set-up-training-targets/runconfig.py

@@ -1,4 +1,6 @@
-# <systemManaged>
+# Code for What's a run configuration 
+
+# <run_system_managed>
 from azureml.core.runconfig import RunConfiguration
 from azureml.core.conda_dependencies import CondaDependencies
 
@@ -6,11 +8,11 @@ run_system_managed = RunConfiguration()
 
 # Specify the conda dependencies with scikit-learn
 run_system_managed.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['scikit-learn'])
-# </systemManaged>
+# </run_system_managed>
 print(run_system_managed)
 
 
-# <user_managed>
+# <run_user_managed>
 from azureml.core.runconfig import RunConfiguration
 
 run_user_managed = RunConfiguration()
@@ -18,6 +20,6 @@ run_user_managed.environment.python.user_managed_dependencies = True
 
 # Choose a specific Python environment by pointing to a Python path. For example: 
 # run_config.environment.python.interpreter_path = '/home/ninghai/miniconda3/envs/sdk2/bin/python'
-# </user_managed>
+# </run_user_managed>
 print(run_user_managed)