Update Explore_Consume_Python_Web_Services.ipynb
Clarify connection.
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@ -20,7 +20,7 @@
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"source": [
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"## Prerequisite\n",
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"\n",
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"In this example, we assume you have already completed [the Quickstart](https://docs.microsoft.com/machine-learning-server/operationalize/python/quickstart-deploy-python-web-service) and there is a web service called 'TxService v1.0' hosted in your instance of Machine Learning Server. \n"
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"In this example, we assume you have already completed [the Publish Quickstart](https://docs.microsoft.com/machine-learning-server/operationalize/python/quickstart-deploy-python-web-service) and there is a web service called 'TxService v1.0' hosted in your instance of Machine Learning Server. \n"
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]
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},
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{
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"\n",
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"1. Import the DeployClient and MLServer classes from the [azureml-model-management-sdk package](https://docs.microsoft.com/en-us/r-server/python-reference/azureml-model-management-sdk/azureml-model-management-sdk) to connect to Machine Learning Server (`use=MLServer`).\n",
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"\n",
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"1. Provide the connection details for your host and context into the corresponding fields. Learn more in the article [Connecting to Machine Learning Server in Python](https://docs.microsoft.com/en-us/r-server/operationalize/python/how-to-authenticate-in-python)."
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"1. Provide **the connection details for your host and context** into the corresponding fields. Learn more in the article [Connecting to Machine Learning Server in Python](https://docs.microsoft.com/en-us/r-server/operationalize/python/how-to-authenticate-in-python)."
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]
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},
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{
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"# -- Define the location of Machine Learning Server --\n",
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"# -- for local onebox: http://localhost:12800\n",
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"HOST = 'http://localhost:12800'\n",
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"context = ('admin', '{{YOUR_PASSWORD}}')\n",
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"context = ('admin', 'YOUR_ADMIN_PASSWORD')\n",
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"client = DeployClient(HOST, use=MLServer, auth=context)"
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]
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},
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