Add examples

Author: Dan Choi

advanced_functionality/pytorch_extending_our_containers/pytorch_extending_our_containers.ipynb

@@ -47,8 +47,8 @@
     "Even if there is direct SDK support for your environment or framework, you may want to add additional functionality or configure your container environment differently while utilizing our container to use on SageMaker.\n",
     "\n",
     "**Some of the reasons to extend a SageMaker deep learning framework container are:**\n",
-    "1. Install additional dependencies, while utilizing the same training and hosting solution.\n",
-    "2. Configure your environment.\n",
+    "1. Install additional dependencies. (E.g. I want to install a specific Python library, that the current SageMaker containers don't install.)\n",
+    "2. Configure your environment. (E.g. I want to add an environment variable to my container.)\n",
     "\n",
     "**Although it is possible to extend any of our framework containers as a parent image, the example this notebook covers is currently only intended to work with our PyTorch (0.4.0+) and Chainer (4.1.0+) containers.**\n",
     "\n",