diff --git a/docs/install_guides/installing-openvino-from-archive-linux.md b/docs/install_guides/installing-openvino-from-archive-linux.md
index 4b1e1d6ec6a..dd54e043aae 100644
--- a/docs/install_guides/installing-openvino-from-archive-linux.md
+++ b/docs/install_guides/installing-openvino-from-archive-linux.md
@@ -15,7 +15,7 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
   * Ubuntu 20.04 long-term support (LTS), 64-bit
 
   .. note::
-     Since the OpenVINO™ 2022.1 release, CentOS 7.6, 64-bit is not longer supported.
+     Since the OpenVINO™ 2022.1 release, CentOS 7.6, 64-bit is no longer supported.
 
 .. tab:: Hardware
 
@@ -42,7 +42,7 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
   * `CMake 3.13 or higher, 64-bit <https://cmake.org/download/>`_
   * GCC 7.5.0 (for Ubuntu 18.04) or GCC 9.3.0 (for Ubuntu 20.04)
   * `Python 3.6 - 3.10, 64-bit <https://www.python.org/downloads/windows/>`_
-     * Note that OpenVINO is gradually stopping the support for Python 3.6. Python 3.7 - 3.10 are recommended. 
+     * Note that OpenVINO is gradually stopping the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10. 
 
 @endsphinxdirective
 
@@ -51,7 +51,7 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 @sphinxdirective
 
 .. important::
-   Before you start your journey with installation of the Intel® Distribution of OpenVINO™ toolkit, we encourage you to check the :ref:`code samples <code samples>` in C, C++, Python and :ref:`notebook tutorials <notebook tutorials>`, so you could see all the amazing things that you can achieve with our tool.
+   Before you start your journey with the installation of the Intel® Distribution of OpenVINO™ toolkit, we encourage you to check the :ref:`code samples <code samples>` in C, C++, Python and :ref:`notebook tutorials <notebook tutorials>`, so you could see all the amazing things that you can achieve with our tool.
 
 @endsphinxdirective
 
@@ -84,11 +84,11 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 
 If you forgot to set the directory in Step 5, you can then use `sudo mv <extracted_folder> /opt/intel` (for root users or administrators), or `mv <extracted_folder> /home/<USER>/intel/` (for regular users) to set that.
 
-For simplicity, it is useful to create a symbolink link:
+For simplicity, it is useful to create a symbolic link/symlink:
 ```sh
 ln -s /home/<USER>/intel/<extracted_folder> /home/<USER>/intel/openvino_2022
 ```
-If such link already exists, remove the previous link with `rm /home/<USER>/intel/openvino_2022`.
+If such a link already exists, remove the previous link with `rm /home/<USER>/intel/openvino_2022`.
 
 The `/opt/intel/openvino_<version>/` or `/home/<USER>/intel/openvino_<version>/` will be referred as the standard OpenVINO `<INSTALL_DIR>` in this document.
 
@@ -104,7 +104,7 @@ source <INSTALL_DIR>/setupvars.sh
 
 If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
 
-> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.
+> **NOTE**: You can also run this script every time you start a new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require a different setup.
 
 The environment variables are set. Next, you can download some additional tools.
 
@@ -112,7 +112,7 @@ The environment variables are set. Next, you can download some additional tools.
 
 Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter can only be installed via PyPI. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
 
-OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on Github](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
+OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on GitHub](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
 
 ### <a name="optional-steps"></a>Step 4 (Optional): Configure Inference on Non-CPU Devices
 
@@ -167,7 +167,7 @@ To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalli
 * Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
 * Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
 * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
-* IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ 
+* IoT libraries and code samples in the GitHub repository: `Intel® IoT Developer Kit`_ 
 
 .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
 
diff --git a/docs/install_guides/installing-openvino-from-archive-macos.md b/docs/install_guides/installing-openvino-from-archive-macos.md
index 4cb2ffae8e4..e936e0faa10 100644
--- a/docs/install_guides/installing-openvino-from-archive-macos.md
+++ b/docs/install_guides/installing-openvino-from-archive-macos.md
@@ -30,8 +30,8 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 .. tab:: Software Requirements
 
   * `CMake 3.13 or higher <https://cmake.org/download/>`_ (choose "macOS 10.13 or later"). Add `/Applications/CMake.app/Contents/bin` to path (for default install). 
-  * `Python 3.6 - 3.9 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.6 - 3.10). Install and add to path.
-     * Note that OpenVINO is gradually stopping the support for Python 3.6. Python 3.7 - 3.10 are recommended.
+  * `Python 3.6 - 3.10 <https://www.python.org/downloads/mac-osx/>`_ (choose 3.6 - 3.10). Install and add to path.
+     * Note that OpenVINO is gradually stopping the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10.
   * Apple Xcode Command Line Tools. In the terminal, run `xcode-select --install` from any directory
   * (Optional) Apple Xcode IDE (not required for OpenVINO™, but useful for development)
 
@@ -65,7 +65,7 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
 
 For simplicity, you can create a symbolic link to the latest installation: `/opt/intel/openvino_2022/`. 
 
-The core components are now installed. Continue to the next section to configure environment.
+The core components are now installed. Continue to the next section to configure the environment.
 
 ### <a name="set-the-environment-variables"></a>Step 2: Configure the Environment
 
@@ -77,7 +77,7 @@ source <INSTALL_DIR>/setupvars.sh
 
 If you have more than one OpenVINO™ version on your machine, you can easily switch its version by sourcing `setupvars.sh` of your choice.
 
-> **NOTE**: You can also run this script every time when you start new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require different setup.
+> **NOTE**: You can also run this script whenever you start a new terminal session. Open `~/.bashrc` in your favorite editor, and add `source <INSTALL_DIR>/setupvars.sh`. Next time when you open a terminal, you will see `[setupvars.sh] OpenVINO™ environment initialized`. Changing `.bashrc` is not recommended when you have many OpenVINO™ versions on your machine and want to switch among them, as each may require a different setup.
 
 The environment variables are set. Continue to the next section if you want to download any additional components.
 
@@ -85,7 +85,7 @@ The environment variables are set. Continue to the next section if you want to d
 
 Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps. 
 
-OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on Github](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
+OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on GitHub](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
 
 ### <a name="configure-ncs2"></a>Step 4 (Optional): Configure the Intel® Neural Compute Stick 2 
 
@@ -113,31 +113,17 @@ To start with C++ samples, see <a href="openvino_docs_OV_UG_Samples_Overview.htm
 
 To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
 
-@sphinxdirective
-.. raw:: html
-
-   </div>
-
-@endsphinxdirective
+## Additional Resources
 
 @sphinxdirective
-
-.. dropdown:: Additional Resources
       
-   * Converting models for use with OpenVINO™: :ref:`Model Optimizer Developer Guide <deep learning model optimizer>`
-   * Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
-   * Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
-   * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
-   * IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ 
+* :ref:`Troubleshooting Guide for OpenVINO Installation & Configuration <troubleshooting guide for install>`
+* Converting models for use with OpenVINO™: :ref:`Model Optimizer User Guide <deep learning model optimizer>`
+* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
+* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
+* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
+* IoT libraries and code samples in the GitHub repository: `Intel® IoT Developer Kit`_ 
 
-<!---
-   To learn more about converting models from specific frameworks, go to:  
-   * :ref:`Convert Your Caffe Model <convert model caffe>`
-   * :ref:`Convert Your TensorFlow Model <convert model tf>`
-   * :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
-   * :ref:`Convert Your Kaldi Model <convert model kaldi>`
-   * :ref:`Convert Your ONNX Model <convert model onnx>`
---->   
-   .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
+.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
 
 @endsphinxdirective
diff --git a/docs/install_guides/installing-openvino-from-archive-windows.md b/docs/install_guides/installing-openvino-from-archive-windows.md
index 94eb9e1c0cd..d8744f8b8ed 100644
--- a/docs/install_guides/installing-openvino-from-archive-windows.md
+++ b/docs/install_guides/installing-openvino-from-archive-windows.md
@@ -39,10 +39,10 @@ You can also check the [Release Notes](https://software.intel.com/en-us/articles
      * `Microsoft Visual Studio 2019 with MSBuild <http://visualstudio.microsoft.com/downloads/>`_
      * `CMake 3.14 or higher, 64-bit <https://cmake.org/download/>`_ (optional, only required for building sample applications)
   * For Python developers: `Python 3.6 - 3.10, 64-bit <https://www.python.org/downloads/windows/>`_
-     * Note that OpenVINO is gradually stopping the support for Python 3.6. Python 3.7 - 3.10 are recommended.
+     * Note that OpenVINO is gradually stopping the support for Python 3.6. You are encouraged to use Python 3.7 - 3.10.
 
   .. note::
-    You can choose to download Community version. Use `Microsoft Visual Studio installation guide <https://docs.microsoft.com/en-us/visualstudio/install/install-visual-studio?view=vs-2019>`_ to walk you through the installation. During installation in the **Workloads** tab, choose **Desktop development with C++**.
+    You can choose to download the Community version. Use `Microsoft Visual Studio installation guide <https://docs.microsoft.com/en-us/visualstudio/install/install-visual-studio?view=vs-2019>`_ to walk you through the installation. During installation in the **Workloads** tab, choose **Desktop development with C++**.
 
   .. note::
     You can either use `cmake<version>.msi` which is the installation wizard or `cmake<version>.zip` where you have to go into the `bin` folder and then manually add the path to environmental variables.
@@ -104,7 +104,7 @@ The environment variables are set. Next, you can download some additional tools.
 
 Since the OpenVINO™ 2022.1 release, the following development tools: Model Optimizer, Post-Training Optimization Tool, Model Downloader and other Open Model Zoo tools, Accuracy Checker, and Annotation Converter are not part of the installer. The OpenVINO™ Development Tools can only be installed via PyPI now. See [Install OpenVINO™ Development Tools](installing-model-dev-tools.md) for detailed steps.
 
-OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on Github](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
+OpenCV is necessary to run demos from Open Model Zoo (OMZ). Some OpenVINO samples can also extend their capabilities when compiled with OpenCV as a dependency. To install OpenCV for OpenVINO, see the [instructions on GitHub](https://github.com/opencv/opencv/wiki/BuildOpenCV4OpenVINO).
 
 ### <a name="optional-steps"></a>Step 4 (Optional): Configure Inference on non-CPU Devices
 
@@ -145,24 +145,17 @@ To start with C++ samples, see <a href="openvino_docs_OV_UG_Samples_Overview.htm
 
 To uninstall the toolkit, follow the steps on the [Uninstalling page](uninstalling-openvino.md).
 
-@sphinxdirective
+## Additional Resources
 
-.. dropdown:: Additional Resources
+@sphinxdirective
       
-   * Converting models for use with OpenVINO™: :ref:`Model Optimizer Developer Guide <deep learning model optimizer>`
-   * Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
-   * Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
-   * Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
-   * IoT libraries and code samples in the GitHUB repository: `Intel® IoT Developer Kit`_ 
-      
-<!---  
-   To learn more about converting models from specific frameworks, go to: 
-   * :ref:`Convert Your Caffe Model <convert model caffe>`
-   * :ref:`Convert Your TensorFlow Model <convert model tf>`
-   * :ref:`Convert Your Apache MXNet Model <convert model mxnet>`
-   * :ref:`Convert Your Kaldi Model <convert model kaldi>`
-   * :ref:`Convert Your ONNX Model <convert model onnx>`
---->    
-   .. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
+* :ref:`Troubleshooting Guide for OpenVINO Installation & Configuration <troubleshooting guide for install>`
+* Converting models for use with OpenVINO™: :ref:`Model Optimizer User Guide <deep learning model optimizer>`
+* Writing your own OpenVINO™ applications: :ref:`OpenVINO™ Runtime User Guide <deep learning openvino runtime>`
+* Sample applications: :ref:`OpenVINO™ Toolkit Samples Overview <code samples>`
+* Pre-trained deep learning models: :ref:`Overview of OpenVINO™ Toolkit Pre-Trained Models <model zoo>`
+* IoT libraries and code samples in the GitHub repository: `Intel® IoT Developer Kit`_ 
+
+.. _Intel® IoT Developer Kit: https://github.com/intel-iot-devkit
 
 @endsphinxdirective