Update README.md

jimmytwei · web-flow · commit 1e259e2cef61 · 2024-08-13T06:58:31.000-07:00
diff --git a/AI-and-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted/README.md b/AI-and-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted/README.md
@@ -24,107 +24,132 @@ In this sample, you will run a batch Linear Regression model with oneDAL daal4py
 | Software                | Intel® oneAPI Data Analytics Library (oneDAL)
 > **Note**: AI and Analytics samples are validated on AI Tools Offline Installer. For the full list of validated platforms refer to [Platform Validation](https://github.com/oneapi-src/oneAPI-samples/tree/master?tab=readme-ov-file#platform-validation).
 
-### For Local Development Environments
+## Key Implementation Details
+
+- This get started sample code is implemented for CPUs using the Python language. The example assumes you have daal4py and scikit-learn installed inside a conda environment, similar to what is delivered with the installation of the Intel® Distribution for Python*.
+
+- The Intel® oneAPI Data Analytics Library (oneDAL) is ready for use once you finish the AI Tools installation and have run the post installation script.
+
+## Environment Setup
 
 You will need to download and install the following toolkits, tools, and components to use the sample.
 
-- **Intel® AI Tools**
+**1. Get AI Tools**
 
-  You can get the AI Tools from [Intel® oneAPI Toolkits](https://www.intel.com/content/www/us/en/developer/tools/oneapi/toolkits.html#analytics-kit). <br> See [*Get Started with the Intel® AI Tools for Linux**](https://www.intel.com/content/www/us/en/develop/documentation/get-started-with-ai-linux) for AI Kit installation information and post-installation steps and scripts.
 
+Required AI Tools: daal4py (Select Intel® Extension for Scikit-learn* on [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html) to install)
 
-## Key Implementation Details
 
-- This get started sample code is implemented for CPUs using the Python language. The example assumes you have daal4py and scikit-learn installed inside a conda environment, similar to what is delivered with the installation of the Intel® Distribution for Python* as part of the Intel® AI Analytics Toolkit.
+If you have not already, select and install these Tools via [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html). AI and Analytics samples are validated on AI Tools Offline Installer. It is recommended to select Offline Installer option in AI Tools Selector.
 
-- The Intel® oneAPI Data Analytics Library (oneDAL) is ready for use once you finish the Intel® AI Analytics Toolkit installation and have run the post installation script.
+>**Note**: If Docker option is chosen in AI Tools Selector, refer to [Working with Preset Containers](https://github.com/intel/ai-containers/tree/main/preset) to learn how to run the docker and samples.
 
-## Environment Setup
+**2. (Offline Installer) Activate the AI Tools bundle base environment**
 
-You will need to download and install the following toolkits, tools, and components to use the sample.
+If the default path is used during the installation of AI Tools:
+```
+source $HOME/intel/oneapi/intelpython/bin/activate
+```
+If a non-default path is used:
+```
+source <custom_path>/bin/activate
+```
+ 
+**3. (Offline Installer) Activate relevant Conda environment**
+<!-- specify relevant conda environment name in Offline Installer for this sample -->
+```
+conda activate base
+``` 
 
-**1. Get Intel® AI Tools**
+**4. Clone the GitHub repository**
+<!-- for oneapi-samples: git clone https://github.com/oneapi-src/oneAPI-samples.git
+cd oneAPI-samples/AI-and-Analytics/<samples-folder>/<individual-sample-folder> -->
+<!-- for migrated samples - provide git clone command for individual repo and cd to sample dir --> 
+``` 
+git clone https://github.com/oneapi-src/oneAPI-samples.git
+cd oneAPI-samples/AI-and-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted
+```
 
-Required AI Tools: Intel® Optimization for XGBoost*
-<br>If you have not already, select and install these Tools via [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html). AI and Analytics samples are validated on AI Tools Offline Installer. It is recommended to select Offline Installer option in AI Tools Selector.
+**5. Install dependencies**
+<!-- It is required to have requirement.txt file in sample dir. It should list additional libraries, such as matplotlib, ipykernel etc. -->
+>**Note**: Before running the following commands, make sure your Conda/Python environment with AI Tools installed is activated
 
-**2. Install dependencies**
 ```
 pip install -r requirements.txt
-```
-**Install Jupyter Notebook** by running `pip install notebook`. Alternatively, see [Installing Jupyter](https://jupyter.org/install) for detailed installation instructions.
+pip install notebook
+``` 
+For Jupyter Notebook, refer to [Installing Jupyter](https://jupyter.org/install) for detailed installation instructions.
 
 ## Run the Sample
->**Note**: Before running the sample, make sure [Environment Setup](https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted#environment-setup) is completed.
+>**Note**: Before running the sample, make sure [Environment Setup](https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/Getting-Started-Samples/INC-Quantization-Sample-for-PyTorch#environment-setup) is completed.
+
 Go to the section which corresponds to the installation method chosen in [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html) to see relevant instructions:
 * [AI Tools Offline Installer (Validated)](#ai-tools-offline-installer-validated)
 * [Conda/PIP](#condapip) 
 * [Docker](#docker)
 
 ### AI Tools Offline Installer (Validated)  
-1. If you have not already done so, activate the AI Tools bundle base environment. If you used the default location to install AI Tools, open a terminal and type the following
-```
-source $HOME/intel/oneapi/intelpython/bin/activate
+
+**1. Register Conda kernel to Jupyter Notebook kernel**
+
+If the default path is used during the installation of AI Tools:
 ```
-If you used a separate location, open a terminal and type the following
+$HOME/intel/oneapi/intelpython/envs/base/bin/python -m ipykernel install --user --name=base
 ```
-source <custom_path>/bin/activate
+If a non-default path is used:
 ```
-2. Activate the Conda environment:
-<!-- specify the name of conda environment for this sample, if there are several options - list all relevant names of environments -->
+<custom_path>/bin/python -m ipykernel install --user --name=base
 ```
-conda activate xgboost
-``` 
-3. Clone the GitHub repository:
-``` 
-git clone https://github.com/oneapi-src/oneAPI-samples.git
-cd oneAPI-samples/AI-and-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted
-```
-4. Launch Jupyter Notebook: 
-> **Note**: You might need to register Conda kernel to Jupyter Notebook kernel, 
-feel free to check [the instruction](https://github.com/IntelAI/models/tree/master/docs/notebooks/perf_analysis#option-1-conda-environment-creation)
+
+**2. Launch Jupyter Notebook** 
+<!-- add other flags to jupyter notebook command if needed, such as port 8888 or allow-root -->
 ```
 jupyter notebook --ip=0.0.0.0
 ```
-<!-- add other flags to jupyter notebook command if needed, such as port 8888 or allow-root -->
-5. Follow the instructions to open the URL with the token in your browser.
-6. Select the Notebook:
+**3. Follow the instructions to open the URL with the token in your browser**
+
+**4. Select the Notebook**
 ```
 IntelPython_daal4py_GettingStarted.ipynb
 ```
-
-7. Change the kernel to xgboost
+**5. Change the kernel to `base`**
  
-8. Run every cell in the Notebook in sequence.
+**6. Run every cell in the Notebook in sequence**
 
 ### Conda/PIP
-> **Note**: Make sure your Conda/Python environment with AI Tools installed is activated
-1. Clone the GitHub repository:
-``` 
-git clone https://github.com/oneapi-src/oneAPI-samples.git
-cd oneapi-samples/AI-and-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted
+> **Note**: Before running the instructions below, make sure your Conda/Python environment with AI Tools installed is activated
+
+**1. Register Conda/Python kernel to Jupyter Notebook kernel** 
+<!-- keep placeholders in this step, user could use any name for Conda/PIP env -->
+For Conda:
+```
+<CONDA_PATH_TO_ENV>/bin/python -m ipykernel install --user --name=<your-env-name>
 ```
+To know <CONDA_PATH_TO_ENV>, run `conda env list` and find your Conda environment path.
 
-2. Launch Jupyter Notebook: 
-> **Note**: You might need to register Conda kernel to Jupyter Notebook kernel, 
-feel free to check [the instruction](https://github.com/IntelAI/models/tree/master/docs/notebooks/perf_analysis#option-1-conda-environment-creation)
+For PIP:
+```
+python -m ipykernel install --user --name=<your-env-name>
+```
+**2. Launch Jupyter Notebook**
+<!-- add other flags to jupyter notebook command if needed, such as port 8888 or allow-root --> 
 ```
 jupyter notebook --ip=0.0.0.0
 ```
-<!-- add other flags to jupyter notebook command if needed, such as port 8888 or allow-root -->
-4. Follow the instructions to open the URL with the token in your browser.
-5. Select the Notebook:
+**3. Follow the instructions to open the URL with the token in your browser**
+
+**4. Select the Notebook**
 ```
-IntelPython_daal4py_GettingStarted.ipynb.ipynb
+IntelPython_daal4py_GettingStarted.ipynb
 ```
+**5. Change the kernel to `<your-env-name>`**
+<!-- leave <your-env-name> as a placeholder as user could choose any name for the env -->
 
-6. Run every cell in the Notebook in sequence.
+**6. Run every cell in the Notebook in sequence**
 
 ### Docker
 AI Tools Docker images already have Get Started samples pre-installed. Refer to [Working with Preset Containers](https://github.com/intel/ai-containers/tree/main/preset) to learn how to run the docker and samples.
 
-
-
 ## Example Output
 
 ```
@@ -161,8 +186,10 @@ Here is one of our loaded model's features:
 ## License
 
 Code samples are licensed under the MIT license. See
-[License.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/License.txt) for details.
+[License.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/License.txt)
+for details.
 
-Third-party program licenses can be found here: [third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt).
+Third party program Licenses can be found here:
+[third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt)
 
 *Other names and brands may be claimed as the property of others. [Trademarks](https://www.intel.com/content/www/us/en/legal/trademarks.html)
