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Add installation section and known issues (#2920)

* Add installation section and known issues

* update wording
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      docs/FAQ.md

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docs/FAQ.md


# Frequently Asked Questions
## Installation problems
### Tensorflow dependency
ML Agents requires TensorFlow; if you don't already have it installed, `pip` will try to install it when you install
the ml-agents package.
If you see a message like this
```console
ERROR: Could not find a version that satisfies the requirement tensorflow<2.0,>=1.7 (from mlagents) (from versions: none)
ERROR: No matching distribution found for tensorflow<2.0,>=1.7 (from mlagents)
```
it means that there is no version of TensorFlow for your python environment. Some known potential causes are:
* You're using 32-bit python instead of 64-bit. See the answer [here](https://stackoverflow.com/a/1405971/224264)
for how to tell which you have installed.
* You're using python 3.8. Tensorflow plans to release packages for this as soon as possible; see
[this issue](https://github.com/tensorflow/tensorflow/issues/33374) for more details.
* You have the `tensorflow-gpu` package installed. This is equivalent to `tensorflow`, however `pip` doesn't recognize
this. The best way to resolve this is to update to `tensorflow==1.15.0` which provides GPU support in the same package
(see the [release notes](https://github.com/tensorflow/tensorflow/issues/33374) for more details.)
* You're on another architecture (e.g. ARM) which requires vendor provided packages.
In all of these cases, the issue is a pip/python environment setup issue. Please search the tensorflow github issues
for similar problems and solutions before creating a new issue.
## Scripting Runtime Environment not setup correctly
If you haven't switched your scripting runtime version from .NET 3.5 to .NET 4.6

## Problems with training on AWS
Please refer to [Training on Amazon Web Service FAQ](Training-on-Amazon-Web-Service.md#faq)
# Known Issues
## Release 0.10.0
* ml-agents 0.10.0 and earlier were incompatible with TensorFlow 1.15.0; the graph could contain
an operator that `tensorflow_to_barracuda` didn't handle. This was fixed in the 0.11.0 release.
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