Capitalization

docs/FAQ.md

 following error message:
 
 ```console
-UnityAgentsException: The brain 3DBallLearning was set to inference mode but the Tensorflow library is not present in the Unity project.
+UnityAgentsException: The brain 3DBallLearning was set to inference mode but the TensorFlow library is not present in the Unity project.
 ```
  This error message occurs because the TensorFlowSharp plugin won't be used
 without the ENABLE_TENSORFLOW flag, refer to [Setting Up The ML-Agents Toolkit
 
 * _Cause_: There may be no LearningBrain with `Control` option checked in the
   `Broadcast Hub` of the Academy. In this case, the environment will not attempt
-  to communicate with python. _Solution_: Click `Add New` in your Academy's
+  to communicate with Python. _Solution_: Click `Add New` in your Academy's
   `Broadcast Hub`, and drag your LearningBrain asset into the `Brains` field,
   and check the `Control` toggle. Also you need to assign this LearningBrain
   asset to all of the Agents you wish to do training on.

docs/Installation-Windows.md

 ```
 
 You may be asked to install new packages. Type `y` and press enter _(make sure
-you are connected to the internet)_. You must install these required packages.
+you are connected to the Internet)_. You must install these required packages.
 The new Conda environment is called ml-agents and uses Python version 3.6.
 
 <p align="center">
 package management system used to install Python packages. Latest versions of
 TensorFlow won't work, so you will need to make sure that you install version
 1.7.1. In the same Anaconda Prompt, type in the following command _(make sure
-you are connected to the internet)_:
+you are connected to the Internet)_:
 
 ```sh
 pip install tensorflow==1.7.1
 cd C:\Downloads\ml-agents\ml-agents
 ```
 
-Make sure you are connected to the internet and then type in the Anaconda
+Make sure you are connected to the Internet and then type in the Anaconda
 Prompt within `ml-agents` subdirectory:
 
 ```sh
 This will complete the installation of all the required Python packages to run
 the ML-Agents toolkit.
 
-Sometimes on Windows, when you use pip to install certain python packages, the pip will get stuck when trying to read the cache of the package. If you see this, you can try:
+Sometimes on Windows, when you use pip to install certain Python packages, the pip will get stuck when trying to read the cache of the package. If you see this, you can try:
 
 ```sh
 pip install -e . --no-cache-dir

docs/Training-Imitation-Learning.md

    as the config parameter, and include the `--run-id` and `--train` as usual. 
    Provide your environment as the `--env` parameter if it has been compiled 
    as standalone, or omit to train in the editor.
-7. (Optional) Observe training performance using Tensorboard.
+7. (Optional) Observe training performance using TensorBoard.
 
 This will use the demonstration file to train a neural network driven agent 
 to directly imitate the actions provided in the demonstration. The environment 

docs/Training-on-Microsoft-Azure.md

 If you've selected to run on a N-Series VM with GPU support, you can verify that
 the GPU is being used by running `nvidia-smi` from the command line.
 
-## Monitoring your Training Run with Tensorboard
+## Monitoring your Training Run with TensorBoard
-Once you have started training, you can [use Tensorboard to observe the
+Once you have started training, you can [use TensorBoard to observe the
 training](Using-Tensorboard.md).  
 
 1. Start by [opening the appropriate port for web traffic to connect to your VM](https://docs.microsoft.com/en-us/azure/virtual-machines/windows/nsg-quickstart-portal).