Intel Python's repositories
scikit-learn_bench
scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for commonly used machine learning algorithms.
numba-dpex
Data Parallel Extension for Numba
mkl-service
Python hooks for Intel(R) Math Kernel Library runtime control settings.
container-images
Dockerfiles for building docker images
mkl_random
Python interface to Intel(R) Math Kernel Library's random number generation functionality
composability_bench
Show effects of over-subscription and ways to fix that
BlackScholes_bench
Benchmark computing Black Scholes formula using different technologies
source-publish
Sources used in Intel Python that have a license that requires publication: GPL, LGPL, MPL
optimizations_bench
Collection of performance benchmarks used to present optimizations implemented for Intel(R) Distribution for Python*
sample-data-parallel-extensions
Sample data parallel extensions built with oneAPI DPC++
xgboost_oneapi
Fork with oneAPI support for XGBoost
devops-tools
Automation tools for IntelPython projects
dpcpp-llvm-spirv
Python package to vendor oneAPI DPC++'s llvm-spirv executable for use by numba-dpex
Intel-Anaconda-Collab
Store notes and wiki for Intel Python and Anaconda SOW collaboration