Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

Building deep learning-powered big data

11:1511:55 Thursday, 25 May 2017
Data science and advanced analytics, Sponsored
Location: Capital Suite 2/3
Secondary topics:  Deep learning

What you'll learn

  • Learn how Intel uses BigDL to build deep learning-powered big data analytics applications


AI plays a central role in the today’s internet applications and emerging intelligent systems, which are driving the need for scalable, distributed big data analytics with deep learning capabilities. There is increasing demand from organizations to discover and explore data using advanced big data analytics and deep learning. BigDL is a distributed deep learning library built on Apache Spark to address the needs for running deep learning workloads on big data clusters, which was developed inside Intel and open sourced to the community in December 2016. Radhika Rangarajan explains how Intel uses BigDL to build deep learning-powered big data analytics applications (object detection, image recognition, NLP, etc.).

This session is sponsored by Intel.

Photo of Radhika Rangarajan

Radhika Rangarajan


Radhika Rangarajan is an engineering director for big data technologies within Intel’s Software and Services Group, where she manages several open source projects and partner engagements, specifically on Apache Spark and machine learning. Radhika is one of the cofounders and the director of the West Coast chapter of Women in Big Data, a grassroots community focused on strengthening the diversity in big data and analytics. Radhika holds both a bachelor’s and a master’s degree in computer science and engineering.