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Applying machine learning to distributed big data analytics plays a central role in today’s intelligent applications and systems. These problem settings have pushed the field to address issues of data scale that were almost inconceivable to AI researchers even a decade ago. To address these challenges, Intel has open sourced Analytics Zoo (https://github.com/intel-analytics/analytics-zoo), which allows users to build and productionize end-to-end Big Data AI pipelines on large-scale Xeon clusters. In this talk, we will show how Analytics Zoo help real-world users (e.g., Burger King, Ant Group, etc.) build end-to-end Big Data AI solutions on Intel Xeon servers. Presented by Jason Dai, Intel Fellow and Chief Architect of Big Data AI, Intel.
Personnel: Jason Dai
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