fix: grammar

sagemaker-pipelines/tabular/caching/sagemaker-pipelines-caching-steps.ipynb

@@ -345,7 +345,7 @@
    "source": [
     "## Define a Pipeline of Parameters and Steps\n",
     "\n",
-    "In this section, combine the steps into a Pipeline so it can be executed.\n",
+    "In this section, combine the steps into a Pipeline, so it can be executed.\n",
     "\n",
     "A pipeline requires a `name`, `parameters`, and `steps`. Names must be unique within an `(account, region)` pair.\n",
     "\n",
@@ -394,7 +394,7 @@
    "id": "673480a3",
    "metadata": {},
    "source": [
-    "For example, you might check the `ProcessingInputs` of the pre-processing step. The Python SDK intentionally structures input code artifacts' S3 paths in order to optimize caching. Before input code files from the local filesystem are uplaoded to S3, they are hashed and the hash is included in the S3 path. A pipeline and step path hierarchy is followed when constructing the entire S3Uri."
+    "For example, you might check the `ProcessingInputs` of the pre-processing step. The Python SDK intentionally structures input code artifacts' S3 paths in order to optimize caching. Before input code files from the local file system are uploaded to S3, they are hashed, and the hash value is included in the S3 path. A pipeline and step path hierarchy is followed when constructing the entire S3Uri."
    ]
   },
   {
@@ -519,7 +519,15 @@
    "id": "89e04224",
    "metadata": {},
    "source": [
-    "**Hint:** To verify whether or a cache hit or cache miss occured for a particular step during a pipeline execution, open the SageMaker resources tab on the left. Click on Pipelines in the dropdown menu and find the \"AbaloneBetaPipelineCaching\" pipeline created in this notebook. Click on the pipeline in order to view the different executions tracked under that pipeline. You can click on each execution to view a graph of the steps and their behavior during that execution. In the graph, click on a step and then click on the \"information\" column to view the cache information."
+    "**Hint:** If you are executing this notebook in SageMaker Studio, use the following tip to easily track caching behavior."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "24d93baf",
+   "metadata": {},
+   "source": [
+    "To verify whether or a cache hit or cache miss occurred for a particular step during a pipeline execution, open the SageMaker resources tab on the left. Click on Pipelines in the dropdown menu and find the \"AbaloneBetaPipelineCaching\" pipeline created in this notebook. Click on the pipeline in order to view the different executions tracked under that pipeline. You can click on each execution to view a graph of the steps and their behavior during that execution. In the graph, click on a step and then click on the \"information\" column to view the cache information."
    ]
   },
   {
@@ -883,9 +891,9 @@
  "metadata": {
   "instance_type": "ml.t3.medium",
   "kernelspec": {
-   "display_name": "Python 3 (Data Science)",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-west-2:236514542706:image/datascience-1.0"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -897,7 +905,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.10"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,