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Powerful Data Science Software Demands Powerful Hardware

Today’s machine learning workloads demand a unique blend of powerful software and hardworking hardware. The open-source ecosystem delivers powerful innovation that data scientists rely on to do their jobs — but without access to powerful compute resources, their models sit idle. Data scientists and developers want hardware to “just work” and IT managers want to govern access and usage to ensure efficiency.

Anaconda's powerful open-source data science software, optimized to run on proven Intel hardware.

Anaconda and Intel are collaborating to build key open-source data science packages optimized for Intel hardware to make machine learning fast and scalable for practitioners everywhere.

Blog Post

Scikit-learn Speed-up with Intel and Anaconda

To deliver the best possible user experience for data science practitioners, popular data science packages and libraries optimized for Intel® oneAPI Math Kernel Library (oneMKL), including NumPy and SciPy, are now easily accessible in the defaults channel of the Anaconda repository.

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