Added some important clarifications about some steps.

There were some important things that should have been mentioned in this tutorial, and it took me a while to figure them out. Most importantly, it was never mentioned how to properly end a training session in the Anaconda prompt to receive an exported .bytes file.

docs/Getting-Started-with-Balance-Ball.md

 every training run are saved to the same directory and will all be included 
 on the same graph.
 
-To summarize, go to your command line, enter the `ml-agents` directory and type: 
+To summarize, go to your Anaconda command line, activate the ml-agents environment, enter the `ml-agents` directory and type: 
 
 ```python
 python3 python/learn.py <env_file_path> --run-id=<run-identifier> --train 
 Once the training process completes, and the training process saves the model 
 (denoted by the `Saved Model` message) you can add it to the Unity project and 
 use it with agents having an **Internal** brain type.
+**Note** You shouldn't just close the unity window once the `Saved Model` message appears. Press Ctrl+C in the Anaconda prompt, and this will formally end the triaing session and export the .byted file. Otherwise,, the byte file will neevr be exported into the ml-agents folder.
 
 ### Setting up TensorFlowSharp Support