oneDAL: Optimize Data Science & Machine Learning with oneAPI

This video gives you a glimpse of the Intel® oneAPI Data Analytics Library (oneDAL). It highlights how oneDAL helps you accelerate machine learning and data science workloads on CPUs and GPUs. It also talks about real-life AI/ML and analytics use cases of oneDAL, and theamazing developer resources provided by Intel’s AI software portfolio powered by oneAPI.

Intel® oneAPI Data Analytics Library (oneDAL) allows AI/ML developers to build high-performance machine learning (ML) and data science workloads. The library is an implementation of the open source oneDAL project and oneAPI specification, which is a part of the UXL Foundation’s open parallel software development ecosystem. It provides optimized versions of various ML and data analytics methods and algorithms (such as linear and logistic regression, Support Vector Machine (SVM), k-means clustering, and more) for an accelerated end-to-end data science pipeline. Apart from Python and C++, it also supports the SYCL programming framework to enable heterogeneous computing and GPU offload.

In addition to the stand-alone version of oneDAL that you can download from the oneDAL product page, the library is also available as a part of the Intel® oneAPI Base Toolkit.

This video will give you a high-level overview of oneDAL and highlight some of its real-world applications. It will showcase some insightful developer resources for you to dive deeper into oneDAL, experiment with it on the latest hardware accelerators on Intel® Tiber™ Developer Cloud platform, and explore Intel’s AI software tools and frameworks optimizations.

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