{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/15"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"},{"label":"System","url":"https://skillfed.io/packages/category/system"}],"enrichment":{"capability":"daal4py provides a Python API to Intel's oneAPI Data Analytics Library, offering optimized implementations of machine learning and data analytics algorithms.","skillfed_tags":["performance-optimization","intel-oneapi","machine-learning"],"use_cases":["Accelerate SVM training and inference on large datasets where CPU optimization is a bottleneck.","Speed up linear regression, logistic regression, and ridge regression on high-dimensional data.","Optimize K-means clustering performance for exploratory data analysis on large point clouds.","Integrate oneDAL algorithms directly into custom ML pipelines that don't rely on scikit-learn.","Benchmark performance of Intel-optimized algorithms against standard implementations."],"what_it_does":"daal4py wraps Intel's oneAPI Data Analytics Library (oneDAL) to provide optimized implementations of machine learning algorithms accessible through a Python API. It targets data scientists and ML practitioners who want to accelerate computationally intensive operations like SVM, linear models, and K-means clustering without rewriting their code. The package depends on daal (the underlying C++ library) and numpy, and is distributed as pre-built wheels for Python 3.9\u20133.12 on Linux (manylinux1) and Windows (x86_64).\n\nHistorically, daal4py offered scikit-learn patching to transparently accelerate scikit-learn calls, but that functionality has been deprecated and moved to a separate package (Intel Extension for Scikit-learn). Current users should treat daal4py as a direct API to oneDAL algorithms rather than a drop-in scikit-learn accelerator.","worth_installing":"Yes, if you need accelerated implementations of specific algorithms (SVM, linear models, K-means) and run on Linux or Windows x86_64. Medium install friction and a stable but slowly-evolving codebase are acceptable tradeoffs for the performance gains. Not recommended if you rely on scikit-learn patching\u2014use Intel Extension for Scikit-learn instead. No known vulnerabilities."},"id":"daal4py","links":{"html":"https://skillfed.io/packages/daal4py","md":"https://skillfed.io/packages/daal4py.md","pypi":"https://pypi.org/project/daal4py/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-09-17","license_spdx":null,"license_treatment":"permissive","name":"daal4py","python_support":"supports_current","summary":"daal4py is a Convenient Python API to the Intel\u00ae oneAPI Data Analytics Library (oneDAL)"},"popularity":{"monthly_downloads":132226,"position":11561,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2024.7.0"}