In this tutorial talk I will introduce Recurrent Neural Networks (RNNs) - used to perform machine learning tasks on temporal data - with an emphasis on explaining the fundamental dynamic models that underly them. A plethora of examples will be given - complete with "soup to nuts" implementations in Python.
Jeremy Watt runs a local ML consultancy called Degree Six and is a Professor at Northwestern where he teaches a range of courses in machine learning, deep learning, mathematical optimization, and reinforcement learning / automatic control. He has just returned to Earth after an intense 18 month stint writing the second edition of his textbook - Machine Learning Refined (published by Cambridge University Press) - which will be released mid-2019.
6:00 p.m - 6:30 p.m is time for social. Seminar will start at 6:30 p.m.
Please note the office security needs to check your government issued ID (Driver License or Passport, please note Student ID is not valid for entry) . Thanks for your understanding.
Our Sponsor: Allstate ( http://www.allstatedatascience.com/ )
Please note we move the Meetup from Suite 875 to Suite 850 (same floor, but on the Allstate-branded side).