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137 changes: 82 additions & 55 deletions ...-Analytics/Getting-Started-Samples/IntelPython_daal4py_GettingStarted/README.md
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Expand Up @@ -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

```
Expand Down Expand Up @@ -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)