update samples from Release-25 as a part of 1.1.2rc0 SDK experimental release (#829)

Co-authored-by: vizhur <vizhur@live.com>

tutorials/image-classification-mnist-data/img-classification-part1-training.ipynb

@@ -126,7 +126,8 @@
       "metadata": {},
       "source": [
         "### Create or Attach existing compute resource\n",
-        "By using Azure Machine Learning Compute, a managed service, data scientists can train machine learning models on clusters of Azure virtual machines. Examples include VMs with GPU support. In this tutorial, you create Azure Machine Learning Compute as your training environment. The code below creates the compute clusters for you if they don't already exist in your workspace.\n",
+        "By using Azure Machine Learning Compute, a managed service, data scientists can train machine learning models on clusters of Azure virtual machines. Examples include VMs with GPU support. In this tutorial, you create Azure Machine Learning Compute as your training environment. You will submit Python code to run on this VM later in the tutorial. \n",
+        "The code below creates the compute clusters for you if they don't already exist in your workspace.\n",
         "\n",
         "**Creation of compute takes approximately 5 minutes.** If the AmlCompute with that name is already in your workspace the code will skip the creation process."
       ]
@@ -263,7 +264,7 @@
       "source": [
         "## Train on a remote cluster\n",
         "\n",
-        "For this task, submit the job to the remote training cluster you set up earlier.  To submit a job you:\n",
+        "For this task, you submit the job to run on the remote training cluster you set up earlier.  To submit a job you:\n",
         "* Create a directory\n",
         "* Create a training script\n",
         "* Create an estimator object\n",