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Speaker "Deep Varma" Details Back

 

Topic

How Visual Search and Computer Vision Are Transforming Real Estate

Abstract

Whether you’re buying or renting, finding a home is a labor- and data-intensive process. Home shoppers who know what they’re looking for (be it marble versus granite countertops, or wood floors versus carpet) still often have to click through every single listing to see if it has the right amenities. They’re left feeling daunted and frustrated. Trulia is changing that. Deep Varma, VP of Engineering at Trulia, will discuss how Trulia is leveraging computer vision to enable visual browsing and create a more personalized experience. This technology is ultimately helping consumers discover a place they’ll love to live. Through computer vision, Trulia has solved real estate’s “filter frustration” by learning a consumer’s home preferences (i.e., wood versus carpet floors) through visual intent, and automatically tailoring recommended listings to each individual’s taste. In utilizing computer vision, Trulia has helped streamline the search process for shoppers, moving them through their journey faster. Specifically, Deep will share: -How to build an image recognition pipeline with a mix of approaches using deep learning and natural language processing -Why visual intent is important, how it will lead to an even more personalized home shopping experience for consumers, and the benefits a business can reap by implementing it -What the future holds for visual search and what its impact will be Attendees will walk away with a key understanding of the importance and effect that visual search, or browsing experience, will have, as well as techniques to help them begin implementing it in their own companies.

Profile

Deep leads all engineering functions across the Trulia business. This includes the frontend teams responsible for building Trulia’s consumer products for mobile, web, and email and other communications, as well as the backend teams focused on analytics, data science, data warehouse, listings and public records acquisition, personalization, search and QA. During his more than 20 years of experience, Deep has focused on building large-scale distributed web, mobile and data platforms with IBM, ABB, Yahoo! and two successful startups. Deep is a graduate of the Haas School of Business at the University of California, Berkeley with a background in Computer Science and Engineering. He lives in the San Francisco Bay Area with his wife and two boys and loves skiing, watching football, reading technical books, building prototypes and learning new technologies.