intel/intel-optimized-ml repository overview

PROJECT NOT UNDER ACTIVE MANAGEMENT. This image repo will no longer be maintained by Intel.

⁠Intel® Optimized ML

Intel® Extension for Scikit-learn*⁠ enhances the performance of Scikit-learn*⁠ by accelerating the training and inference of machine learning models on Intel® hardware.

XGBoost*⁠ is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable.

⁠Images

The images below include Intel® Extension for Scikit-learn*⁠ and XGBoost*⁠.

The images below additionally include Jupyter Notebook⁠ server:

⁠Run the Jupyter Container

docker run -it --rm \
    -p 8888:8888 \
    --net=host \
    -v $PWD/workspace:/workspace \
    -w /workspace \
    intel/intel-optimized-ml:2024.2.0-xgboost-2.0.3-pip-jupyter

After running the command above, copy the URL (something like http://127.0.0.1:$PORT/?token=***) into your browser to access the notebook server.

⁠Images with Intel® Distribution for Python*

The images below include [Intel® Distribution for Python*]:

The images below additionally include Jupyter Notebook⁠ server:

⁠Build from Source

To build the images from source, clone the AI Containers⁠ repository, follow the main README.md file to setup your environment, and run the following command:

cd classical-ml
docker compose build ml-base
docker compose run ml-base

You can find the list of services below for each container in the group:

⁠License

View the License⁠ for the Intel® Distribution for Python⁠.

The images below also contain other software which may be under other licenses (such as Pytorch*, Jupyter*, Bash, etc. from the base).

It is the image user's responsibility to ensure that any use of The images below comply with any relevant licenses for all software contained within.

* Other names and brands may be claimed as the property of others.