@@ -1,15 +1,17 @@
 
-[!(Intel® Distribution for Python*)](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html) is a cluster of packages that includes Numba*, NumPy* and more. All these packages are optimized via [!(Intel® oneAPI Math Kernel Library (oneMKL))](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html#gs.ddfdq4) and [!(Intel® oneAPI Data Analytics Library (oneDAL))](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onedal.html) to make the Python* application more efficient. The distribution includes a multitude of popular components, some of which include:
+[Intel® Distribution for Python*](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html) is a cluster of packages that includes Numba*, NumPy* and more. All these packages are optimized via [Intel® oneAPI Math Kernel Library (oneMKL](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html#gs.ddfdq4) and [Intel® oneAPI Data Analytics Library (oneDAL](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onedal.html) to make the Python* application more efficient. The distribution includes a multitude of popular components, some of which include:
 
 Libraries:
 - Python
-- numPy
+- NumPy
 - SciPy
+
 Mkl interfaces:
 - Mkl-service
 - Mkl-random
 - Mkl-fft
 - Mkl-umath
+
 GPU components:
 - Dpctl
 - Dpnp
@@ -20,22 +22,26 @@ GPU components:
 CPUs:
 - Intel® Core™ processor family
 - Intel® Xeon® processor family
+
 GPUs:
 - Intel® UHD Graphics for 11th generation Intel processors or newer
 - Intel® Iris® Xᵉ graphics
 - Intel® Arc™ graphics
 - Intel® Data Center GPU Flex Series
 - Intel® Data Center GPU Max Series
+
 Operating systems:
 - Unix family*
 - Windows® 10
 - Windows* 11
 - pported versions:
 - Python 3.11, Python 3.12
+
 Package management:
 - conda*
 - Pip
-- mamba
+- Mamba
+
 Compatible with:
 - VS Code
 - Jupyter Notebook
@@ -44,39 +50,46 @@ Compatible with:
 
 ## Supported Installation Options
 
-The Intel ® Distribution for Python* supports several installation options
+The Intel® Distribution for Python* supports several installation options
 
 Supported operating systems are outlined under System Requirements.
-You may select the components you wish to install. The full list of components in the Intel® Distribution for Python* is outlined on the landing page section [!(What’s Included)](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html).
+You may select the components you wish to install. The full list of components in the Intel® Distribution for Python* is outlined on the landing page section [What’s Included](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html).
 
-## GPU USers
-You can use [!(Intel® Distribution for Python* in  Intel® Tiber™ Developer Cloud)](https://www.intel.com/content/www/us/en/developer/tools/devcloud/services.html). After getting access to the cloud system, follow the instructions below to install Intel® Distribution for Python* with one of the available installation options.
+## GPU Users
+You can use [Intel® Distribution for Python* in  Intel® Tiber™ Developer Cloud](https://www.intel.com/content/www/us/en/developer/tools/devcloud/services.html). After getting access to the cloud system, follow the instructions below to install Intel® Distribution for Python* with one of the available installation options.
 
 ## Offline Installer
-1. To download Intel Distribution for Python*, visit here and choose the installation method of your choice. 
+1. To download the Intel® Distribution for Python*, visit [here](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-python-download.html) and choose the installation method of your choice. 
 2. Run the following commands to install on respective platform:
+
+**Linux installation (Interactive)**
+Note that the file name must be changed to how to appears in your downloads folder.
 ```bash
-# Linux installation (Interactive) 
-# Note that the file name must be changed to how to appears in your downloads folder.
 bash ~/intelpython3-202X.X.X.sh 
+```
 
-# Linux installation (CLI) 
+**Linux installation (CLI)**
+```bash
 bash ~/intelpython3.sh -b -u -p ~/intelpython3 
+```
+The flags can be included as necessary. They are used as follows:
+-b enables batch mode, running the installation without interactive prompts.
+-u updates the current installation. You may omit this if this is the first time you’re installing IDP on this machine.
+-p specifies the installation path prefix. In this example, ~/intelpython3 is the target directory.
 
-# The flags can be included as necessary. They are used as follows:
-# -b enables batch mode, running the installation without interactive prompts.
-# -u updates the current installation. You may omit this if this is the first time you’re installing IDP on this machine.
-# -p specifies the installation path prefix. In this example, ~/intelpython3 is the target directory.
-
-# Windows installation (Interactive) 
+**Windows installation (Interactive)**
+```bash
 intelpython3.exe 
+```
 
-# Windows installation (CLI) 
+**Windows installation (CLI)**
+```bash
 start /wait intelpython3.exe /S /RegisterPython=0 /D=%LOCALAPPDATA%\intelpython3 
 ```
 
-3. Activate the conda environment.
-*Linux*
+3. Activate the conda environment on your respective platform.
+
+**Linux**
 The following commands can be used to activate the Intel® Distribution for Python installation:
 ```bash
 #Root access or Intel(R) Developer Cloud installation*
@@ -86,61 +99,84 @@ source /opt/intel/intelpython3/bin/activate
 source $HOME/intelpython3/bin/activate
 ```
 
-*Windows*
-Navigate to the installation directory of Intel Python and find the "Scripts" directory, then run `.\activate` in the terminal. This runs the base activate script found at
-`C:/User/path/to/intelpython3\Scripts\activate`
+**Windows**
+Navigate to the installation directory of Intel Python and find the "Scripts" directory, then run `.\activate` in the terminal.
 
-The command prompt should point to installation when running `where python`
-`(base) C:/User/path/to/intelpython3`
+The command prompt should now show `(base)` at the start of the command prompt.
+
+4. Verify instalaltion.
+```bash
+conda list
+```
+
+**Deactivating environment for Offline Installer**
+To deactivate your IDP environment, run the command below until base env is deactivated.
+
+```bash
+conda deactivate
+```
 
-Installation verification – `conda list`
-   
-*Deactivating environment for Offline Installer*
-To deactivate your IDP environment, run `conda deactivate` until base env is deactivated
-`conda deactivate`
 
 ## Conda
 1. Follow conda Installation Guide to install conda in your environment. If you already have conda installed in your system, update it with the command: 
-`conda update conda `
+```bash
+conda update conda
+```
 2. Add Intel channel and conda-forge to tell conda to choose Intel packages over default packages when available.
 ```bash
 conda config --add channels https://software.repos.intel.com/python/conda/
 conda config --add channels conda-forge
-
-# Remove defaults channel from .condarc if it exists
+```
+Remove defaults channel from .condarc if it exists
+```bash
 conda config --remove channels defaults
 ```
-3. Install Intel® Distribution for Python* via conda. We recommend that you create a new environment while installing. To install the core python3 environment, run the following command: 
+3. Install Intel® Distribution for Python* via conda. We recommend that you create a new environment while installing. To install the python3 environment, run the following command: 
 `conda create -n idp intelpython3_full python=3.x`
 Please note that “x” in “python=3.x” should signify which version of Python* you would like to install. For example, for Python* version 3.9: 
-`conda create -n idp intelpython3_core python=3.9`
-For individual installation commands, refer to the [!(What’s included](https://www.intel.com/content/www/us/en/developer/articles/tool/whats-included-distribution-for-python.html#packageEnvironmentManagers) section.
+`conda create -n idp intelpython3_full python=3.9`
+
+>For individual installation commands, refer to the [What’s included](https://www.intel.com/content/www/us/en/developer/articles/tool/whats-included-distribution-for-python.html#packageEnvironmentManagers) section.
 4. Activate the conda environment:
-`conda activate idp` 
+```bash
+conda activate idp
+```
 
 ## Mamba
-1.	If you do not have Mamba, get Miniforge by following the instructions here 
-`conda update mamba`
+1.	If you do not have Mamba, get Miniforge by following the instructions [here](https://github.com/conda-forge/miniforge?tab=readme-ov-file#install). Otherwise, ensure that it is updated:
+```bash
+conda update mamba
+```
 2.	Add Intel channel and conda-forge to tell conda to choose Intel packages over default packages, when available.
 ```bash
 conda config --add channels https://software.repos.intel.com/python/conda/
 conda config --add channels conda-forge
-
-# Remove defaults channel from .condarc if it exists
+```
+Remove defaults channel from .condarc if it exists.
+```bash
 conda config --remove channels defaults
 ```
 3.	Install Intel® Distribution for Python* via Mamba. We recommend that you create a new environment while installing. To install the core python3 environment, run the following command: 
-`mamba create -n idp intelpython3_full python=3.x`
-Please note that “x” in “python=3.x” should signify which version of Python* you would like to install. 
+```bash
+mamba create -n idp intelpython3_full python=3.x
+```
+Please note that “x” in `python=3.x` should signify which version of Python* you would like to install. 
+
 4.	Acitvate conda environment, then follow the usual steps for activating the environment: 
+```bash
 mamba activate idp
-5.	Installation verification
-`mamba list	`
+```
+5.	Verify installation.
+```bash
+mamba list	
+```
 
 ## Docker
-1.	If you don’t have Docker installed on your machine, follow [!(these instructions)](https://docs.docker.com/engine/install/) to install it.
-2.	Pull the image from [!(DockerHub)](https://hub.docker.com/r/intel/python) using the following command:
-`docker pull intel/python:latest `
+1.	If you don’t have Docker installed on your machine, follow [these instructions](https://docs.docker.com/engine/install/) to install it.
+2.	Pull the image from [DockerHub](https://hub.docker.com/r/intel/python) using the following command:
+```bash
+docker pull intel/python:latest 
+```
 3.	Run a performance sample by running the following commands:
 ```bash
 git clone https://github.com/intel/ai-containers
@@ -150,27 +186,14 @@ docker run --rm -it \
     intel/python:latest \
     python /tests/perf_sample.py
 ```
-4. Installation verification
-`conda list`
-
-## Proof of Concept
-You can see the benefits of using the Intel® Distribution for Python* on your own machine by comparing a simple program’s runtime between both distributions. First, run the sample code below in your new Intel® Distribution for Python* environment, and take note of the total runtime which should be displayed in the output. 
+4. Verify installation.
 ```bash
-import numpy as np
-import time
-
-start = time.time()
-
-rd = np.random.RandomState(88)
-a = rd.randint(1,1000,(1000,1000))
-y = rd.randint(1,1000,(1000))
-res = np.linalg.solve(a,y)
+conda list
+```
 
-end = time.time()
+## Example with NumPy
+You can see the benefits of using the Intel® Distribution for Python* on your own machine by comparing a simple program’s runtime between both distributions. First, run the sample code below in your new Intel® Distribution for Python* environment, and take note of the total runtime which should be displayed in the output. 
 
-print(res)
-print('Time Consuming:',end-start)
-```
 
 Once you have taken note of the runtime of this program, switch the environment back to stock Python* and run the script again. Compare the runtime in the stock environment to the runtime in the Intel® distribution environment. You should see the benefits provided by the Intel® Distribution for Python* through the significantly decreased runtime.
 
@@ -182,16 +205,17 @@ this]
 No special modifications to your existing Python* projects are required to start using them with this toolkit. You can refer to samples on GitHub to learn more about this distribution.#
 
 ## Profiling Python Code
-- [!(Intel® VTune™ Profiler)](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html)
-- [!(•	Intel® Advisor)](https://www.intel.com/content/www/us/en/developer/tools/oneapi/advisor.html)
+- [Intel® VTune™ Profiler](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html)
+- [Intel® Advisor](https://www.intel.com/content/www/us/en/developer/tools/oneapi/advisor.html)
 
 ## Additional Resources
-- [!(Data Parallel Extension for NumPy* documentation)](https://intelpython.github.io/dpnp/)
-- [!(Data Parallel Control Library* documentation  )](https://intelpython.github.io/dpctl/latest/index.html)
-- [!(Data Parallel Extension for Numba* documentation)](https://intelpython.github.io/numba-dpex/latest/index.html)
+- [What's Included](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html)
+- [Data Parallel Extension for NumPy* documentation](https://intelpython.github.io/dpnp/)
+- [Data Parallel Control Library* documentation](https://intelpython.github.io/dpctl/latest/index.html)
+- [Data Parallel Extension for Numba* documentation](https://intelpython.github.io/numba-dpex/latest/index.html)
 
 ## Support
-If you have further questions or need support on your workload optimization, please submit your queries to the [!(Intel® Distribution for Python* Forum)](https://community.intel.com/t5/Intel-Distribution-for-Python/bd-p/distribution-python) or [!(Intel® Distribution for Python* GitHub)](https://github.com/IntelPython), on the Issues or Discussions pages, depending on the type of support required.
+If you have further questions or need support on your workload optimization, please submit your queries to the [Intel® Distribution for Python* Forum](https://community.intel.com/t5/Intel-Distribution-for-Python/bd-p/distribution-python) or [Intel® Distribution for Python* GitHub](https://github.com/IntelPython), on the Issues or Discussions pages, depending on the type of support required.
 
 ## Notices and Disclaimers
 Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.