A simplified API to Intel(R) oneAPI Data Analytics Library that allows for fast usage of the framework suited for Data Scientists or Machine Learning users. Built to help provide an abstraction to Intel(R) oneAPI Data Analytics Library for either direct usage or integration into one's own framework.

We publish blogs on Medium, so follow us to learn tips and tricks for more efficient data analysis the help of daal4py. Here are our latest blogs:

• Intel Gives Scikit-Learn the Performance Boost Data Scientists Need
• From Hours to Minutes: 600x Faster SVM
• Improve the Performance of XGBoost and LightGBM Inference
• Accelerate Kaggle Challenges Using Intel AI Analytics Toolkit
• Accelerate Your scikit-learn Applications
• Accelerate Linear Models for Machine Learning
• Accelerate K-Means Clustering

• Documentation
• scikit-learn API and patching
• Building from Sources
• About Intel(R) oneAPI Data Analytics Library

Report issues, ask questions, and provide suggestions using:

• GitHub Issues
• GitHub Discussions
• Forum

You may reach out to project maintainers privately at onedal.maintainers@intel.com

daal4py is available at the Python Package Index, on Anaconda Cloud in Conda-Forge channel and in Intel channel.

# PyPI (recommended by default)
pip install daal4py

# Anaconda Cloud from Conda-Forge channel (recommended for conda users by default)
conda install daal4py -c conda-forge

# Intel channel (recommended for Intel® Distribution for Python users)
conda install daal4py -c https://software.repos.intel.com/python/conda/

⚠️ Note: GPU and MPI support are optional dependencies. Required dependencies for GPU and MPI support will not be downloaded. You need to manually install dpcpp_cpp_rt package for GPU support and impi_rt package for MPI support.

# PyPi for dpcpp
pip install --upgrade dpcpp_cpp_rt

# PyPi for MPI
pip install --upgrade impi_rt

# Anaconda Cloud for dpcpp
conda install dpcpp_cpp_rt -c intel

# Anaconda Cloud for MPI
conda install impi_rt -c intel