removing include/merging with docs

Author: Blackmist

articles/machine-learning/includes/machine-learning-low-pri-vm.md

@@ -141,7 +141,8 @@ compute_target.wait_for_completion(show_output=True, min_node_count=None)
 # print(compute_target.get_status().serialize())
 ```
 
-[!INCLUDE [low-pri-note](../includes/machine-learning-low-pri-vm.md)]
+> [!NOTE]
+> You may choose to use [low-priority VMs](../how-to-manage-optimize-cost.md#low-pri-vm) to run some or all of your workloads. See how to [create a low-priority VM](how-to-create-attach-compute-cluster.md#lower-your-compute-cluster-cost-with-low-priority-vms). 
 
 ### Configure and submit training job
 

articles/machine-learning/includes/machine-learning-py38-ignore.md

@@ -278,7 +278,8 @@ except ComputeTargetException:
 
 When the creation process finishes, you train your model. For more information, see [Select and use a compute target for training](how-to-set-up-training-targets.md).
 
-[!INCLUDE [low-pri-note](../includes/machine-learning-low-pri-vm.md)]
+> [!NOTE]
+> You may choose to use [low-priority VMs](../how-to-manage-optimize-cost.md#low-pri-vm) to run some or all of your workloads. See how to [create a low-priority VM](how-to-create-attach-compute-cluster.md#lower-your-compute-cluster-cost-with-low-priority-vms). 
 
 ## Azure Databricks
 

articles/machine-learning/v1/how-to-monitor-tensorboard.md

@@ -123,7 +123,8 @@ except ComputeTargetException:
     compute_target.wait_for_completion(show_output=True, min_node_count=None, timeout_in_minutes=20)
 ```
 
-[!INCLUDE [low-pri-note](../includes/machine-learning-low-pri-vm.md)]
+> [!NOTE]
+> You may choose to use [low-priority VMs](../how-to-manage-optimize-cost.md#low-pri-vm) to run some or all of your workloads. See how to [create a low-priority VM](how-to-create-attach-compute-cluster.md#lower-your-compute-cluster-cost-with-low-priority-vms). 
 
 For more information on compute targets, see the [what is a compute target](../concept-compute-target.md) article.
 

articles/machine-learning/v1/how-to-secure-training-vnet.md

@@ -117,7 +117,8 @@ except ComputeTargetException:
 
 If you instead want to create a CPU cluster, provide a different VM size to the vm_size parameter, such as STANDARD_D2_V2.
 
-[!INCLUDE [low-pri-note](../includes/machine-learning-low-pri-vm.md)]
+> [!NOTE]
+> You may choose to use [low-priority VMs](../how-to-manage-optimize-cost.md#low-pri-vm) to run some or all of your workloads. See how to [create a low-priority VM](how-to-create-attach-compute-cluster.md#lower-your-compute-cluster-cost-with-low-priority-vms). 
 
 For more information on compute targets, see the [what is a compute target](../concept-compute-target.md) article.
 

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

@@ -123,7 +123,8 @@ except ComputeTargetException:
     compute_target.wait_for_completion(show_output=True, min_node_count=None, timeout_in_minutes=20)
 ```
 
-[!INCLUDE [low-pri-note](../includes/machine-learning-low-pri-vm.md)]
+> [!NOTE]
+> You may choose to use [low-priority VMs](../how-to-manage-optimize-cost.md#low-pri-vm) to run some or all of your workloads. See how to [create a low-priority VM](how-to-create-attach-compute-cluster.md#lower-your-compute-cluster-cost-with-low-priority-vms).
 
 For more information on compute targets, see the [what is a compute target](../concept-compute-target.md) article.
 

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

@@ -94,7 +94,8 @@ if not compute_name in ws.compute_targets :
 compute_target = ws.compute_targets[compute_name]
 ```
 
-[!INCLUDE [low-pri-note](../includes/machine-learning-low-pri-vm.md)]
+> [!NOTE]
+> You may choose to use [low-priority VMs](../how-to-manage-optimize-cost.md#low-pri-vm) to run some or all of your workloads. See how to [create a low-priority VM](how-to-create-attach-compute-cluster.md#lower-your-compute-cluster-cost-with-low-priority-vms).
 
 The intermediate data between the data preparation and the automated ML step can be stored in the workspace's default datastore, so we don't need to do more than call `get_default_datastore()` on the `Workspace` object. 
 

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

@@ -274,7 +274,8 @@ Select **Save and run script in terminal**  to run the *run-pytorch-data.py* scr
 
 This code will print a URL to the experiment in the Azure Machine Learning studio. If you go to that link, you'll be able to see your code running.
 
-[!INCLUDE [amlinclude-info](../includes/machine-learning-py38-ignore.md)]
+> [!NOTE]
+> You may see some warnings starting with *Failure while loading azureml_run_type_providers...*. You can ignore these warnings. Use the link at the bottom of these warnings to view your output.
 
 
 ### Inspect the log file

articles/machine-learning/v1/how-to-use-automlstep-in-pipelines.md

@@ -154,7 +154,8 @@ Here's a description of how the control script works:
 
 1. Once you're authenticated, you'll see a link in the terminal. Select the link to view the job.
 
-    [!INCLUDE [amlinclude-info](../includes/machine-learning-py38-ignore.md)]
+   > [!NOTE]
+   > You may see some warnings starting with *Failure while loading azureml_run_type_providers...*. You can ignore these warnings. Use the link at the bottom of these warnings to view your output.
 
 ## View the output