update samples from Release-132 as a part of 1.0.48 SDK release

Author: vizhur

Diff for: configuration.ipynb

@@ -58,7 +58,7 @@
         "\n",
         "### What is an Azure Machine Learning workspace\n",
         "\n",
-        "An Azure ML Workspace is an Azure resource that organizes and coordinates the actions of many other Azure resources to assist in executing and sharing machine learning workflows.  In particular, an Azure ML Workspace coordinates storage, databases, and compute resources providing added functionality for machine learning experimentation, deployment, inferencing, and the monitoring of deployed models."
+        "An Azure ML Workspace is an Azure resource that organizes and coordinates the actions of many other Azure resources to assist in executing and sharing machine learning workflows.  In particular, an Azure ML Workspace coordinates storage, databases, and compute resources providing added functionality for machine learning experimentation, deployment, inference, and the monitoring of deployed models."
       ]
     },
     {
@@ -103,7 +103,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.0.45 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.0.48 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -258,7 +258,7 @@
         "```shell\n",
         "az vm list-skus -o tsv\n",
         "```\n",
-        "* min_nodes - this sets the minimum size of the cluster.  If you set the minimum to 0 the cluster will shut down all nodes while note in use.  Setting this number to a value higher than 0 will allow for faster start-up times, but you will also be billed when the cluster is not in use.\n",
+        "* min_nodes - this sets the minimum size of the cluster.  If you set the minimum to 0 the cluster will shut down all nodes while not in use.  Setting this number to a value higher than 0 will allow for faster start-up times, but you will also be billed when the cluster is not in use.\n",
         "* max_nodes - this sets the maximum size of the cluster.  Setting this to a larger number allows for more concurrency and a greater distributed processing of scale-out jobs.\n",
         "\n",
         "\n",

Diff for: configuration.yml

@@ -0,0 +1,4 @@
+name: configuration
+dependencies:
+- pip:
+  - azureml-sdk

Diff for: contrib/datadrift/azure-ml-datadrift.ipynb

@@ -33,10 +33,9 @@
       "source": [
         "## Install the DataDrift package\n",
         "\n",
-        "Install the azureml-contrib-datadrift, azureml-contrib-opendatasets and lightgbm packages before running this notebook.\n",
+        "Install the azureml-contrib-datadrift, azureml-opendatasets and lightgbm packages before running this notebook.\n",
         "```\n",
         "pip install azureml-contrib-datadrift\n",
-        "pip install azureml-contrib-datasets\n",
         "pip install lightgbm\n",
         "```"
       ]
@@ -63,7 +62,7 @@
         "import pandas as pd\n",
         "import requests\n",
         "from azureml.contrib.datadrift import DataDriftDetector, AlertConfiguration\n",
-        "from azureml.contrib.opendatasets import NoaaIsdWeather\n",
+        "from azureml.opendatasets import NoaaIsdWeather\n",
         "from azureml.core import Dataset, Workspace, Run\n",
         "from azureml.core.compute import AksCompute, ComputeTarget\n",
         "from azureml.core.conda_dependencies import CondaDependencies\n",
@@ -259,8 +258,7 @@
         "trainingDataset = Dataset.auto_read_files(dpath, include_path=True)\n",
         "trainingDataset = trainingDataset.register(workspace=ws, name=dataset_name, description=\"dset\", exist_ok=True)\n",
         "\n",
-        "trainingDataSnapshot = trainingDataset.create_snapshot(snapshot_name=snapshot_name, compute_target=None, create_data_snapshot=True)\n",
-        "datasets = [(Dataset.Scenario.TRAINING, trainingDataSnapshot)]\n",
+        "datasets = [(Dataset.Scenario.TRAINING, trainingDataset)]\n",
         "print(\"dataset registration done.\\n\")\n",
         "datasets"
       ]
@@ -574,6 +572,22 @@
         "        time.sleep(3)"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "We need to wait up to 10 minutes for the Model Data Collector to dump the model input and inference data to storage in the Workspace, where it's used by the DataDriftDetector job."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "time.sleep(600)"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},

Diff for: contrib/datadrift/azure-ml-datadrift.yml

@@ -0,0 +1,8 @@
+name: azure-ml-datadrift
+dependencies:
+- pip:
+  - azureml-sdk
+  - azureml-contrib-datadrift
+  - azureml-opendatasets
+  - lightgbm
+  - azureml-widgets

Diff for: how-to-use-azureml/automated-machine-learning/automl_env.yml

@@ -2,6 +2,7 @@ name: azure_automl
 dependencies:
   # The python interpreter version.
   # Currently Azure ML only supports 3.5.2 and later.
+- pip
 - python>=3.5.2,<3.6.8
 - nb_conda
 - matplotlib==2.1.0