[Example] Update cpp example README (#13280)

* update the README to solve the  library cannot find problem

* fix the broken format

* remove redundancy and broken format

* add .

cpp-package/example/README.md

@@ -20,15 +20,15 @@ The makefile will also download the necessary data files and store in a data fol
 
 ## Examples
 
-This directory contains following examples. In order to run the examples, ensure that the path to the MXNet shared library is added to the OS specific environment variable viz. **LD\_LIBRARY\_PATH** for Linux, Mac and Ubuntu OS and **PATH** for Windows OS.
+This directory contains following examples. In order to run the examples, ensure that the path to the MXNet shared library is added to the OS specific environment variable viz. **LD\_LIBRARY\_PATH** for Linux, Mac and Ubuntu OS and **PATH** for Windows OS. For example `export LD_LIBRARY_PATH=/usr/local/cuda/lib64:/home/ubuntu/incubator-mxnet/lib` on ubuntu using gpu.
 
 ### [alexnet.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/alexnet.cpp>)
 
 The example implements the C++ version of AlexNet. The networks trains on MNIST data. The number of epochs can be specified as a command line argument. For example to train with 10 epochs use the following:
 
-	```
-	build/alexnet 10
-	```
+```
+build/alexnet 10
+```
 
 ### [googlenet.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/googlenet.cpp>)
 
@@ -97,7 +97,7 @@ build/lenet_with_mxdataiter 10
 
 In addition, there is `run_lenet_with_mxdataiter.sh` that downloads the mnist data and run `lenet_with_mxdataiter` example.
 
-###[inception_bn.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/inception_bn.cpp>)
+### [inception_bn.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/inception_bn.cpp>)
 
 The code implements an Inception network using the C++ API with batch normalization. The example uses MNIST data to train the network. The model trains for 100 epochs. The example can be run by executing the following command: