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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.
Event Speakers:
Irina Rish, Research Staff, IBM T.J. Watson Research Center
Abstract: Learning About Brain: Sparse Modeling and Beyond
Alex Smola, Professor in the Machine Learning Department, Carnegie Mellon University
Abstract: Fast, Cheap and Deep - Scaling Machine Learning
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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