"We are elated to leverage the power of CPU instances provided by Azure* Machine Learning to enable developers and data scientists to take advantage of Intel® AI optimizations powered by Intel® hardware. By integrating optimizations such as the Intel® Extension for Scikit-learn* powered by oneAPI into the platform, users can easily accelerate development and deployment of machine learning workloads for faster results and achieve a reduction in resource costs with just a few lines of code."
— Vijay Aski, partner director AI Platform, Microsoft*
"The Intel team's optimization of fMRI and PadChest models using Intel® Extension for PyTorch* and OpenVINO™ toolkit powered by oneAPI, leading to approximately 6x increase in performance, tailored for medical imaging, showcases best practices that do more than just accelerate running times. These enhancements not only cater to the unique demands of medical image processing but also offer the potential to reduce overall costs and bolster scalability."
— Santamaria-Pang Alberto, principal applied data scientist, Health AI at Microsoft
Maximize & Scale Azure Machine Learning Models with Intel AI Frameworks
A Closer Look at MLOps and the Intel Extension for Scikit-learn within Azure Machine Learning