Sr. Principle Engineer, Intel
Jason is currently a Sr. Principle Engineer and Chief Architect of Big Data Technologies at Intel, leading the development of advanced Big Data analytics (incl. distributed machine learning and deep learning). He is an internationally recognized expert on big data, cloud and distributed machine learning; he is the co-chair of Strata Data Conference Beijing, a committer and PMC member of Apache Spark project, and the chief architect of BigDL project (https://github.com/intel-analytics/BigDL/), a distributed deep learning framework on Apache Spark.
2:35pm–3:15pm Tuesday, September 19, 2017
Very large-scale distributed deep learning on BigDL
Location: Imperial B
Secondary topics: Data science and AI, Deep learning, Tools and frameworks
Jason Dai (Intel), Ding Ding (Intel)
BigDL is an open source distributed deep learning framework built for Big Data platform. By leveraging the cluster distribution capabilities in Apache Spark, BigDL successfully unleashes the power of large-scale distributed training in deep learning which not only has good performance and ability to efficiently scale on large clusters but also has good convergence result.