Minor text updates.

caffe/README.md

@@ -16,7 +16,7 @@ or one or more custom layers can be written in Python.
 The `mnist_cmd` sub-directory contains configuration and job scripts for running 
 Caffe as a command line tool with only built-in layers. This example represents use 
 case 1 as described above. The `lenet_solver.prototxt` and `lenet_train_test.prototxt` 
-were taken from the MNIST examples directory available in the Caffe repository available 
+were taken from the MNIST examples directory available in the Caffe repository 
 [here](https://github.com/BVLC/caffe/tree/master/examples/mnist). Minor changes have 
 been made just so the path to the input dataset is correct. The `caffe` command 
 in the job submission scripts can be modified as follows to run training on 

datasets/README.md

@@ -8,9 +8,9 @@ maintained by the respective framework developers, as these are the same samples
 uses when getting started with the framework. 
 
 However, the original examples are designed to automatically download the required 
-dataset in a framework-defined directory. This is not a feasible option as compute 
-nodes on the supercomputers do not have access to the Internet. Therefore, the samples 
-have been slightly modified to load data from this `datasets` directory. It contains 
+dataset in a framework-defined directory. This is not a feasible option when working 
+with supercomputers as compute nodes do not have access to the Internet. Therefore, the 
+samples have been slightly modified to load data from this `datasets` directory. It contains 
 the MNIST dataset in different formats because samples for different frameworks expect 
 the dataset in a different format.