Using Crowdsourced Images to Create a Image Recognition Model with BigDL

Talk Description:

Volunteers around the world increasingly act as human sensors to collect millions of data points. A team from the World Bank trained deep learning models, using Apache Spark and BigDL, to confirm that photos gathered through a crowdsourced data collection pilot matched the goods for which observations were submitted.

In this talk, Maurice Nsabimana, a statistician at the World Bank, will demonstrate a collaborative project to design and train large-scale deep learning models using crowdsourced images from around the world. BigDL is a distributed deep learning library designed from the ground up to run natively on Apache Spark. It enables data engineers and scientists to write deep learning applications in Scala or Python as standard Spark programs-without having to explicitly manage distributed computations. Attendees of this session will learn how to get started with BigDL, which runs in any Apache Spark environment, whether on-premises or in the Cloud.

Speakers:

• Maurice Nsabimana (World Bank Development Data Group)
• Jennie Wang (Intel)

Agenda:

6:30 pm Food, Drinks and Networking
7:00 pm Welcome and Introductions - Dave Nielsen
7:15 pm Main Talk Begins "Using Crowdsourced Images to Create a Image Recognition Model with BigDL" by Maurice Nsabimana of the World Bank & Jennie Wang of Intel
8:15 pm Q&A