Merge pull request #101587 from v-qquaidjoha/main

Updated the occurrences of py36 to py37

Author: jborsecnik

articles/machine-learning/how-to-train-with-custom-image.md

@@ -101,7 +101,7 @@ fastai_env.docker.base_dockerfile = "./Dockerfile"
 > Azure Machine Learning only supports Docker images that provide the following software:
 > * Ubuntu 18.04 or greater.
 > * Conda 4.7.# or greater.
-> * Python 3.6+.
+> * Python 3.7+.
 > * A POSIX compliant shell available at /bin/sh is required in any container image used for training. 
 
 For more information about creating and managing Azure Machine Learning environments, see [Create and use software environments](how-to-use-environments.md). 

articles/machine-learning/v1/how-to-auto-train-image-models-v1.md

@@ -45,7 +45,7 @@ Automated ML supports model training for computer vision tasks like image classi
     * [Install the `automl` package yourself](https://github.com/Azure/azureml-examples/blob/main/v1/python-sdk/tutorials/automl-with-azureml/README.md#setup-using-a-local-conda-environment), which includes the [default installation](/python/api/overview/azure/ml/install#default-install) of the SDK.
 
     > [!NOTE]
-    > Only Python 3.6 and 3.7 are compatible with automated ML support for computer vision tasks. 
+    > Only Python 3.7 and 3.8 are compatible with automated ML support for computer vision tasks. 
 
 ## Select your task type
 Automated ML for images supports the following task types:

articles/machine-learning/v1/how-to-deploy-inferencing-gpus.md

@@ -147,7 +147,7 @@ name: project_environment
 dependencies:
   # The Python interpreter version.
   # Currently Azure ML only supports 3.5.2 and later.
-- python=3.6.2
+- python=3.7
 
 - pip:
   # You must list azureml-defaults as a pip dependency
@@ -292,4 +292,4 @@ aks_target.delete()
 
 * [Deploy model on FPGA](how-to-deploy-fpga-web-service.md)
 * [Deploy model with ONNX](../concept-onnx.md#deploy-onnx-models-in-azure)
-* [Train TensorFlow DNN Models](../how-to-train-tensorflow.md)
+* [Train TensorFlow DNN Models](../how-to-train-tensorflow.md)

articles/machine-learning/v1/how-to-train-keras.md

@@ -140,7 +140,7 @@ First, define your conda dependencies in a YAML file; in this example the file i
 channels:
 - conda-forge
 dependencies:
-- python=3.6.2
+- python=3.7
 - pip:
   - azureml-defaults
   - tensorflow-gpu==2.0.0

articles/machine-learning/v1/how-to-train-pytorch.md

@@ -167,7 +167,7 @@ First, define your conda dependencies in a YAML file; in this example the file i
 channels:
 - conda-forge
 dependencies:
-- python=3.6.2
+- python=3.7
 - pip=21.3.1
 - pip:
   - azureml-defaults

articles/machine-learning/v1/how-to-train-scikit-learn.md

@@ -86,7 +86,7 @@ You can also create your own custom environment. Define your conda dependencies
 
 ```yaml
 dependencies:
-  - python=3.6.2
+  - python=3.7
   - scikit-learn
   - numpy
   - pip:

articles/machine-learning/v1/how-to-train-tensorflow.md

@@ -176,7 +176,7 @@ First, define your conda dependencies in a YAML file; in this example the file i
 channels:
 - conda-forge
 dependencies:
-- python=3.6.2
+- python=3.7
 - pip:
   - azureml-defaults
   - tensorflow-gpu==2.2.0

articles/machine-learning/v1/tutorial-1st-experiment-sdk-train.md

@@ -164,7 +164,7 @@ First you'll create a file with the package dependencies.
         - defaults
         - pytorch
     dependencies:
-        - python=3.6.2
+        - python=3.7
         - pytorch
         - torchvision
     ```
@@ -357,7 +357,7 @@ channels:
     - defaults
     - pytorch
 dependencies:
-    - python=3.6.2
+    - python=3.7
     - pytorch
     - torchvision
     - pip

articles/machine-learning/v1/tutorial-auto-train-image-models-v1.md

@@ -43,7 +43,7 @@ You'll write code using the Python SDK in this tutorial and learn the following
 
 * If you don’t have an Azure subscription, create a free account before you begin. Try the [free or paid version](https://azure.microsoft.com/free/) of Azure Machine Learning today.
 
-* Python 3.6 or 3.7 are supported for this feature
+* Python 3.7 or 3.8 are supported for this feature
 
 * Complete the [Quickstart: Get started with Azure Machine Learning](../quickstart-create-resources.md#create-the-workspace) if you don't already have an Azure Machine Learning workspace.
 

articles/machine-learning/v1/tutorial-pipeline-python-sdk.md

@@ -292,7 +292,7 @@ Create a file `conda_dependencies.yml` with the following contents:
 
 ```yml
 dependencies:
-- python=3.6.2
+- python=3.7
 - pip:
   - azureml-core
   - azureml-dataset-runtime