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MLconf ATL 2017

MLconf- The Machine Learning Conference

Friday, September 15, 2017 from 9:00 AM to 6:00 PM (EDT)

MLconf ATL 2017

Ticket Information

Ticket Type Sales End Price Fee Quantity
General Admission Ticket I to MLconf ATL 2017 Aug 1, 2017 $200.00 $11.99

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Event Details

MLconf was created to host the thought leaders in Machine Learning and Data Science to discuss their most recent experience with applying techniques, tools, algorithms and methodologies to the seemingly impossible problems that occur when dealing with massive and noisy data. MLconf is independent of any outside company or university – it’s simply a conference organized to gather the Machine Learning communities in various cities to share knowledge and create an environment for the community to coalesce.

Aran Khanna, Software Engineer, Amazon Web Services 


Le Song, Assistant Professor, College of Computing, Georgia Institute of Technology


Jacob Eisenstein, Assistant Professor, School of Interactive Computing, Georgia Institute of Technology


Jennifer Marsman, Principal Software Development Engineer, Microsoft


Qiaoling Liu, Lead Data Scientist, CareerBuilder


Tim Chartier, Chief Academic Officer, Tresata


Alexandra Johnson, Software Engineer, SigOpt


Robert Morris, CTO and Co-Founder, Predikto, Inc.

Venkatesh Ramanathan, Data Scientist, PayPal 


Talha Obaid, Email Security, Symantec 


Jeremy Nixon, Machine Learning Engineer, Spark Technology Center 


Jessica Rudd, PhD Student, Analytics and Data Science, Kennesaw State University


 Ryan West, Machine Learning Engineer, Nexosis 


 Anna Kiefer, Software Engineer, Kevala Analytics



Gold:, HiringSolved, Nexosis, Amazon 


Silver: SigOpt

Publishers: CRC Press 

Have questions about MLconf ATL 2017? Contact MLconf- The Machine Learning Conference

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When & Where

The Academy of Medicine
875 W Peachtree St NE
Atlanta, GA 30309

Friday, September 15, 2017 from 9:00 AM to 6:00 PM (EDT)

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MLconf- The Machine Learning Conference

MLconf gathers communities to discuss the recent research and application of Algorithms, Tools, and Platforms to solve the hard problems that exist within organizing and analyzing massive and noisy data sets.

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