Maurice of the World Bank, and Jennie Wang from Intel, have completed the Image Recognition project this group started last year. It is now running on a large, distributed cluster using the Jupyter Notebook this group created. Many thanks to Ashley, Alex, Goutham, Rashim, Sujee, Neal and Nico who contributed time and thoughtfulness to get this project to a completed Proof-Of-Concept. And congrats to Jennie and Maurice for finishing it.
Talk Description: Using Crowdsourced Images to Create a Image Recognition Model with BigDL
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.
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