update windows installation & links (#14905)

docs/install_guides/configurations-for-iei-card.md

@@ -19,7 +19,7 @@ Using the IEI Mustang-V100-MX8 requires downloading and installing the most curr
 Visit the [IEI Download Center](https://download.ieiworld.com/) for the most current software and documentation.
 Search for **Mustang-V100-MX8**.
 
-Download the appropriate software for your system, decompress the downloaded archive, enter the newly created directory, and run the install script:
+Download the appropriate software for your system, extract the downloaded archive file, enter the newly created directory, and run the install script:
 
 On **Linux**:
 -  Run the `install.sh script` with `sudo`, or as `root`.

docs/install_guides/configurations-for-intel-gpu.md

@@ -11,7 +11,7 @@
 
 ## Linux
 
-If you have installed OpenVINO Runtime from the archive file, follow these steps to work with GPU:
+If you have installed OpenVINO Runtime from the archive file, APT, or YUM, follow these steps to work with GPU:
 
 1. Go to the install_dependencies directory:
    ```sh

docs/install_guides/installing-openvino-from-archive-windows.md

@@ -1,6 +1,6 @@
 # Install OpenVINO™ Runtime on Windows from an Archive File {#openvino_docs_install_guides_installing_openvino_from_archive_windows}
 
-With the OpenVINO™ 2022.2 release, you can download and use archive files to install OpenVINO Runtime. The archive files contain pre-built binaries and library files needed for OpenVINO Runtime, as well as code samples. 
+With the OpenVINO™ 2022.3 release, you can download and use archive files to install OpenVINO Runtime. The archive files contain pre-built binaries and library files needed for OpenVINO Runtime, as well as code samples. 
 
 Installing OpenVINO Runtime from archive files is recommended for C++ developers. If you are working with Python, the PyPI package has everything needed for Python development and deployment on CPU and GPUs. See the [Install OpenVINO from PyPI](installing-openvino-pip.md) page for instructions on how to install OpenVINO Runtime for Python using PyPI.
 
@@ -65,29 +65,29 @@ See the [Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNo
    ```
    > **NOTE**: `C:\Program Files (x86)\Intel` is the recommended folder. You may also use a different path if desired or if you don't have administrator privileges on your computer.
 
-2. Download the [OpenVINO Runtime archive file for Windows](https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/windows/) to your local `Downloads` folder.
+2. Download the [OpenVINO Runtime archive file for Windows](https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3/windows/) to your local `Downloads` folder.
    
    If you prefer using command-lines, run the following commands in the command prompt window you opened:
    ```sh
    cd <user_home>/Downloads
-   curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.2/windows/w_openvino_toolkit_windows_2022.2.0.7713.af16ea1d79a_x86_64.zip --output openvino_2022.2.0.7713.zip
+   curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3/windows/w_openvino_toolkit_windows_2022.3.0.9052.9752fafe8eb_x86_64.zip --output openvino_2022.3.0.zip
    ```
-   > **NOTE**: A `.sha256` file is provided together with the archive file to validate your download process. To do that, download the `.sha256` file from the same repository and run `CertUtil -hashfile openvino_2022.2.0.7713.zip SHA256`. Compare the returned value in the output with what's in the `.sha256` file: if the values are the same, you have downloaded the correct file successfully; if not, create a Support ticket [here](https://www.intel.com/content/www/us/en/support/contact-intel.html).
+   > **NOTE**: A `.sha256` file is provided together with the archive file to validate your download process. To do that, download the `.sha256` file from the same repository and run `CertUtil -hashfile openvino_2022.3.0.zip SHA256`. Compare the returned value in the output with what's in the `.sha256` file: if the values are the same, you have downloaded the correct file successfully; if not, create a Support ticket [here](https://www.intel.com/content/www/us/en/support/contact-intel.html).
 
 
-3. Use your favorite tool to extract the archive file, rename the extracted folder as `openvino_2022.2.0.7713`, and move it to the `C:\Program Files (x86)\Intel` directory.
+3. Use your favorite tool to extract the archive file, rename the extracted folder, and move it to the `C:\Program Files (x86)\Intel` directory.
    
    To do this step using command-lines, run the following commands in the command prompt window you opened:
    ```sh
-   tar -xf openvino_2022.2.0.7713.zip
+   tar -xf openvino_2022.3.0.zip
-   ren w_openvino_toolkit_windows_2022.2.0.7713.af16ea1d79a_x86_64 openvino_2022.2.0.7713
+   ren w_openvino_toolkit_windows_2022.3.0.9052.9752fafe8eb_x86_64 openvino_2022.3.0
-   move openvino_2022.2.0.7713 "C:\Program Files (x86)\Intel"
+   move openvino_2022.3.0 "C:\Program Files (x86)\Intel"
    ```
 
 4. For simplicity, it is useful to create a symbolic link. Open a command prompt window as administrator (see Step 1 for how to do this) and run the following commands:
    ```sh
    cd C:\Program Files (x86)\Intel
-   mklink /D openvino_2022 openvino_2022.2.0.7713
+   mklink /D openvino_2022 openvino_2022.3.0
    ```
    > **NOTE**: If you have already installed a previous release of OpenVINO 2022, a symbolic link to the `openvino_2022` folder may already exist. If you want to override it, nagivate to the `C:\Program Files (x86)\Intel` folder and delete the existing linked folder before running the `mklink` command.
 
@@ -144,16 +144,16 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
 @sphinxdirective
 .. tab:: Get started with Python
 
-   Try the `Python Quick Start Example <https://docs.openvino.ai/2022.2/notebooks/201-vision-monodepth-with-output.html>`_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+   Try the `Python Quick Start Example <https://docs.openvino.ai/nightly/notebooks/201-vision-monodepth-with-output.html>`_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
    
    .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
       :width: 400
 
    Visit the :ref:`Tutorials <notebook tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
    
-   * `OpenVINO Python API Tutorial <https://docs.openvino.ai/2022.2/notebooks/002-openvino-api-with-output.html>`_
+   * `OpenVINO Python API Tutorial <https://docs.openvino.ai/nightly/notebooks/002-openvino-api-with-output.html>`_
-   * `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2022.2/notebooks/001-hello-world-with-output.html>`_
+   * `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/nightly/notebooks/001-hello-world-with-output.html>`_
-   * `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2022.2/notebooks/205-vision-background-removal-with-output.html>`_
+   * `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/nightly/notebooks/205-vision-background-removal-with-output.html>`_
 
 .. tab:: Get started with C++
 

docs/install_guides/installing-openvino-linux.md

@@ -1,8 +1,10 @@
 # Install OpenVINO™ Runtime on Linux from Installer
 
-Currently only the following ways are provided to install OpenVINO™:
+Currently the following ways are provided to install OpenVINO™:
 
 * [Install OpenVINO Runtime from an Archive File](installing-openvino-from-archive-linux.md)
+* [Install OpenVINO Runtime from APT](@ref openvino_docs_install_guides_installing_openvino_apt)
+* [Install OpenVINO Runtime from YUM](@ref openvino_docs_install_guides_installing_openvino_yum)
 * [Install OpenVINO from PyPI](installing-openvino-pip.md)
 * [Install OpenVINO with Docker](installing-openvino-docker-linux.md)
 * [Build From Source](https://github.com/openvinotoolkit/openvino/wiki/BuildingCode)

docs/install_guides/installing-openvino-pip.md

@@ -86,13 +86,13 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
 
 <img src="https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif" width=400>
 
-Try the [Python Quick Start Example](https://docs.openvino.ai/2022.2/notebooks/201-vision-monodepth-with-output.html) to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+Try the [Python Quick Start Example](https://docs.openvino.ai/nightly/notebooks/201-vision-monodepth-with-output.html) to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
 
 ### Get started with Python
 Visit the [Tutorials](../tutorials.md) page for more Jupyter Notebooks to get you started with OpenVINO, such as:
-* [OpenVINO Python API Tutorial](https://docs.openvino.ai/2022.2/notebooks/002-openvino-api-with-output.html)
+* [OpenVINO Python API Tutorial](https://docs.openvino.ai/nightly/notebooks/002-openvino-api-with-output.html)
-* [Basic image classification program with Hello Image Classification](https://docs.openvino.ai/2022.2/notebooks/001-hello-world-with-output.html)
+* [Basic image classification program with Hello Image Classification](https://docs.openvino.ai/nightly/notebooks/001-hello-world-with-output.html)
-* [Convert a PyTorch model and use it for image background removal](https://docs.openvino.ai/2022.2/notebooks/205-vision-background-removal-with-output.html)
+* [Convert a PyTorch model and use it for image background removal](https://docs.openvino.ai/nightly/notebooks/205-vision-background-removal-with-output.html)
 
 ### Run OpenVINO on accelerated devices
 OpenVINO Runtime has a plugin architecture that enables you to run inference on multiple devices without rewriting your code. Supported devices include integrated GPUs, discrete GPUs, NCS2, VPUs, and GNAs. Visit the [Additional Configurations](configurations-header.md) page for instructions on how to configure your hardware devices to work with OpenVINO.