Integrate UAT fixes (#5517)

* Added info on DockerHub CI Framework

* Feature/azaytsev/change layout (#3295)

* Changes according to feedback comments

* Replaced @ref's with html links

* Fixed links, added a title page for installing from repos and images, fixed formatting issues

* Added links

* minor fix

* Added DL Streamer to the list of components installed by default

* Link fixes

* Link fixes

* ovms doc fix (#2988)

* added OpenVINO Model Server

* ovms doc fixes

Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>

* Updated openvino_docs.xml

* Edits to MO

Per findings spreadsheet

* macOS changes

per issue spreadsheet

* Fixes from review spreadsheet

Mostly IE_DG fixes

* Consistency changes

* Make doc fixes from last round of review

* integrate changes from baychub/master

* Update Intro.md

* Update Cutting_Model.md

* Update Cutting_Model.md

* Fixed link to Customize_Model_Optimizer.md

Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
Co-authored-by: baychub <cbay@yahoo.com>

inference-engine/ie_bridges/python/sample/hello_classification/README.md

@@ -27,7 +27,7 @@ each sample step at [Integration Steps](../../../../../docs/IE_DG/Integrate_with
 
 ## Running
 
-Run the application with the <code>-h</code> option to see the usage message:
+Run the application with the `-h` option to see the usage message:
 
 ```sh
 python hello_classification.py -h
@@ -68,7 +68,7 @@ To run the sample, you need specify a model and image:
 >
 > - The sample accepts models in ONNX format (.onnx) that do not require preprocessing.
 
-You can do inference of an image using a pre-trained model on a GPU using the following command:
+For example, to perform inference of an image using a pre-trained model on a GPU, run the following command:
 
 ```sh
 python hello_classification.py -m <path_to_model>/alexnet.xml -i <path_to_image>/cat.bmp -d GPU