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.
Watch the entire presentation at https://techfieldday.com/appearance/intel-presents-at-ai-field-day-2/ or visit https://TechFieldDay.com/event/aifd2/ or https://intel.com/ai for more information.
