update samples from Release-169 as a part of SDK release

update samples from Release-168 as a part of  SDK release

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

@@ -11,11 +11,10 @@ dependencies:
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=latest
-  - azureml-defaults~=latest
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/latest/validated_win32_requirements.txt [--no-deps]
+  - azureml-widgets~=1.48.0
+  - azureml-defaults~=1.48.0
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.48.0/validated_win32_requirements.txt [--no-deps]
   - matplotlib==3.6.2
   - xgboost==1.3.3
   - arch==4.14
   - mlflow-skinny==1.30.0
-

how-to-use-azureml/deployment/production-deploy-to-aks-gpu/production-deploy-to-aks-gpu.ipynb

@@ -240,9 +240,9 @@
         "# Please see [Azure ML Containers repository](https://github.com/Azure/AzureML-Containers#featured-tags)\n",
         "# for open-sourced GPU base images.\n",
         "env.docker.base_image = DEFAULT_GPU_IMAGE\n",
-        "env.python.conda_dependencies = CondaDependencies.create(python_version=\"3.6.2\", \n",
+        "env.python.conda_dependencies = CondaDependencies.create(python_version=\"3.6.2\", pin_sdk_version=False,\n",
         "                                    conda_packages=['tensorflow-gpu==1.12.0','numpy'],\n",
-        "                                    pip_packages=['azureml-contrib-services', 'azureml-defaults'])\n",
+        "                                    pip_packages=['azureml-contrib-services==1.47.0', 'azureml-defaults==1.47.0'])\n",
         "\n",
         "inference_config = InferenceConfig(entry_script=\"score.py\", environment=env)\n",
         "aks_config = AksWebservice.deploy_configuration()\n",
@@ -343,7 +343,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.6.6"
+      "version": "3.7.0"
     }
   },
   "nbformat": 4,

how-to-use-azureml/deployment/spark/model-register-and-deploy-spark.ipynb

@@ -137,7 +137,7 @@
         "myenv = Environment('my-pyspark-environment')\r\n",
         "myenv.docker.base_image = \"mcr.microsoft.com/mmlspark/release:0.15\"\r\n",
         "myenv.inferencing_stack_version = \"latest\"\r\n",
-        "myenv.python.conda_dependencies = CondaDependencies.create(pip_packages=[\"azureml-core\",\"azureml-defaults\",\"azureml-telemetry\",\"azureml-train-restclients-hyperdrive\",\"azureml-train-core\"], python_version=\"3.6.2\")\r\n",
+        "myenv.python.conda_dependencies = CondaDependencies.create(pip_packages=[\"azureml-core\",\"azureml-defaults\",\"azureml-telemetry\",\"azureml-train-restclients-hyperdrive\",\"azureml-train-core\"], python_version=\"3.7.0\")\r\n",
         "myenv.python.conda_dependencies.add_channel(\"conda-forge\")\r\n",
         "myenv.spark.packages = [SparkPackage(\"com.microsoft.ml.spark\", \"mmlspark_2.11\", \"0.15\"), SparkPackage(\"com.microsoft.azure\", \"azure-storage\", \"2.0.0\"), SparkPackage(\"org.apache.hadoop\", \"hadoop-azure\", \"2.7.0\")]\r\n",
         "myenv.spark.repositories = [\"https://mmlspark.azureedge.net/maven\"]\r\n"
@@ -341,7 +341,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.6.2"
+      "version": "3.7.0"
     }
   },
   "nbformat": 4,