.. _other_intel_python_projects:
Intel provides a number of Python* packages which allow you to get the best performance and scalability of numercial, scientific, and data analytics applications. Some of these projects listed below.
| Package Name | Description |
|---|---|
| numpy | Numpy* accelerated with Intel® MKL |
| scikit-learn | Scikit-Learn* accelerated with Intel® Data Analytics Library |
| mkl_fft | Python interfaces for Intel® MKL FFT functionality |
| mkl_random | Python interfaces for Intel® MKL random number generation functionality |
| mkl_service | Python interfaces for Intel® MKL service functions |
| daal4py | Python interfaces for Intel® Data Analytics Library |
| smp | Python module for composable multi-processing and multi-threading |
| sdc | Numba* compiler extension for Pandas* |
Optimized versions of community projects may dramatically boost performance of Python* codes with minimum to no required code changes. Visit benchmarks webpage for more details.
Intel also directly upstream optimizations to some open source projects such as XGBoost* and Numba*.
For more information please visit Intel® Distribution for Python* product page.