Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Sergey Ermolin

Sergey Ermolin
Solutions Architect and TPM, Deep Learning, Spark Analytics, and Big Data Technologies, Intel

Website

Sergey Ermolin is a software solutions architect for deep learning, Spark analytics, and big data technologies at Intel. A Silicon Valley veteran with a passion for machine learning and artificial intelligence, Sergey has been interested in neural networks since 1996, when he used them to predict aging behavior of quartz crystals and cesium atomic clocks made by Hewlett-Packard. Sergey holds an MSEE and a certificate in mining massive datasets from Stanford and BS degrees in both physics and mechanical engineering from California State University, Sacramento.

Sessions

16:35–17:15 Wednesday, 23 May 2018
Using Siamese CNNs for removing duplicate entries from real estate listing databases
Big data and data science in the cloud, Data science and machine learning
 Location: Capital Suite 13 Level: Intermediate
Secondary topics:  Data Integration and Data Pipelines sessions, Media, Advertising, Entertainment
Sergey Ermolin (Intel), Olga Ermolin (MLS Listings)
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Aggregation of geospecific real estate databases results in duplicate entries for properties located near geographical boundaries. Sergey Ermolin and Olga Ermolin detail an approach for identifying duplicate entries via the analysis of images that accompany real estate listings that leverages a transfer learning Siamese architecture based on VGG-16 CNN topology. Read more.