#1 IT Conference Calendar

Deep Learning World

05/31/2020 - 06/04/2020

Caesars Palace
Las Vegas, Nevada

Event Website:

Event Details

Deep Learning World

May 31-June 4, 2020 (Speaking days June 2-3)

Venue: Caesars Palace, Las Vegas
Speaker proposal deadline: November 27, 2019
Speakers will be notified by: February 6, 2020

DLW is the premier conference covering the commercial deployment of deep learning. The event delivers case studies, keynote addresses from the preeminent top names, comprehensive coverage of deep learning application areas across industries, and actionable guidance for hands-on practitioners.

Deploying today’s state-of-the-art. DLW’s mission is to foster breakthroughs in the value-driven operationalization of established deep learning methods. The event achieves this by focusing more on industry applications than on R&D or academic advancement. Commercial projects do have much in common with many research projects — but the difference is, commercial projects are executed in order to solve specific, current industrial problems, and the models have been veritably used to that end by way of their operational deployment.

World class instruction. Training workshop options and select conference sessions at DLW cover the principles behind deep learning and its commercial deployment.

Co-located with PAW. DLW 2020 — May 31-June 4 in Las Vegas — will be held simultaneously alongside the Predictive Analytics World events PAW Business, PAW Financial, PAW Industry 4.0, and PAW Healthcare. Speakers will receive complimentary registration to access all DLW and PAW sessions, and regular attendees will be provided access to cross-registration options.

About the founding program chair, Luba Gloukhova. As a research analytics consultant at Stanford Graduate School of Business, Luba facilitates and accelerates advanced research projects at a major R&D hub of the Silicon Valley. She supports Stanford GSB faculty by conceiving and generating innovative solutions that drive their cutting edge research. Luba received her master’s in analytics from the University of San Francisco and her bachelors in both applied math and economics from Berkeley. Before her current position in academic research, she gained industry experience in analytics consulting, high frequency trading analysis, catastrophe risk modeling, and quantitative marketing. Luba also teaches yoga and enjoys an active lifestyle.

Browse by Month

Browse by Year

Search by Location

City or State

Search by title