cosmetic

examples/docker/README.md

-*Dockerfile"* is a simple template that shows how to install the latest Apex on top of an existing image.  Edit *Dockerfile* to choose a base image, then run 
+**Dockerfile** is a simple template that shows how to install the latest Apex on top of an existing image.  Edit **Dockerfile** to choose a base image, then run 
 ```
 docker build -t image_with_apex ."
 ```
-.  If you want to rebuild your image, and force the latest Apex to be cloned and installed, make any small change to the "SHA" variable on line 8.
+.  If you want to rebuild your image, and force the latest Apex to be cloned and installed, make any small change to the `SHA` variable on line 8.
 
-*base_images.md* provides guidance on base images to use in the `FROM <base image>` line of *Dockerfile*.
+**base_images.md** provides guidance on base images to use in the `FROM <base image>` line of **Dockerfile**.
 
 Instead of building a new container, it is also a viable option to clone Apex on bare metal, mount the Apex repo into your container at launch by running, for example,
 ```

examples/docker/base_images.md

@@ -2,7 +2,7 @@ When specifying
 ```
 FROM <base image>
 ```
-in *Dockerfile*, `<base image>` must have Pytorch and CUDA installed.
+in **Dockerfile**, `<base image>` must have Pytorch and CUDA installed.
 
 If you have an NGC account, you can use Nvidia's official Pytorch container
 ```
@@ -19,6 +19,6 @@ docker build -t my_pytorch_image -f docker/pytorch/Dockerfile .
 ```
 `my_pytorch_image` will contain CUDA, and can be used as `<base image>`.
 
-Warning:
+**Warning:**
 Currently, Pytorch's latest stable image on Dockerhub
 [pytorch/pytorch:0.4_cuda9_cudnn7](https://hub.docker.com/r/pytorch/pytorch/tags/) contains Pytorch installed with prebuilt binaries.  It does not contain NVCC, which means it is not an eligible candidate for `<base image>`.