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This is on top of this PR. Thanks for the contribution from #1294.

@xiaomaogy xiaomaogy requested a review from mmattar October 9, 2018 23:51
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</p>

## Windows installation
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Should keep the header "Windows Users"

guide](Installation-Windows.md) to setting up your env. For Mac and Linux,
continue with this guide.

## Clone the ML-Agents Toolkit Repository
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This header should be renamed to "## Mac and Unix Users", immediately follows by a sub-heading "### Clone the ML-Agents Toolkit Repository"

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Further, below:

  • ## Install Python and mlagents Package --> ### Install Python and mlagents Package
  • ### NOTES --> **Notes:** (bold instead of header)
  • Delete ### Mac and Unix Users header

These suggested are following the thinking that the intention here is to have three top-level sections:

  • Windows Users
  • Mac and Unix Users
  • Docker Installation

@xiaomaogy xiaomaogy self-assigned this Oct 10, 2018
…, added the package explanation to the Windows installation doc
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Hi @mmattar , I've resolved all of your comments.

To use the ML-Agents toolkit, you install Python and the required Python
packages as outlined below. This guide also covers how set up GPU-based training
(for advanced users). GPU-based training is not required for the v0.4 release of
(for advanced users). GPU-based training is not required for the v0.6 release of
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On second thought, can we just remove v0.6 and say "for the current release"

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More appropriately .... "GPU-based training is not currently required for the ML-Agents toolkit."

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Fixed.

check Nvidia's page [here](https://developer.nvidia.com/cuda-gpus).

As of the ML-Agents toolkit v0.4, only CUDA v9.0 and cuDNN v7.0.5 is supported.
As of the ML-Agents toolkit v0.6, only CUDA v9.0 and cuDNN v7.0.5 is supported.
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similar to above - remove the v0.6 as we'll always need to uptick

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Fixed both places.


The `UnitySDK` subdirectory contains the Unity Assets to add to your projects.
It also contains many [example environments](Learning-Environment-Examples.md)
that can be used to help get you familiar with Unity.
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"that can be used to help get you familiar with Unity." --> "to help you get started."

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Fixed, I also fixed the exact same wording in the Installation.md doc.

If you don't want to use Git, you can always directly download all the files
[here](https://github.com/Unity-Technologies/ml-agents/archive/master.zip).

The `UnitySDK` subdirectory contains the Unity Assets to add to your projects.
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Why are we referring to the SDK as assets?

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I copied over the same sentences in the Installation doc to this Installation windows doc. Also they can be considered as Assets since they are something we can put in the Asset store. (And are compatible with the Asset usage, while the python package isn't).

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@mmattar I've resolved all of the comments.

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@xiaomaogy - one minor fix - otherwise 👍 - Thanks.

check Nvidia's page [here](https://developer.nvidia.com/cuda-gpus).

As of the ML-Agents toolkit v0.6, only CUDA v9.0 and cuDNN v7.0.5 is supported.
Currently for ML-Agents toolkit, only CUDA v9.0 and cuDNN v7.0.5 is supported.
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Currently for --> Currently for the

@xiaomaogy xiaomaogy merged commit 0c06ebf into develop Oct 11, 2018
@awjuliani awjuliani deleted the develop-has-taiar-patch-1 branch October 11, 2018 20:17
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2 participants