Generative Adversarial Networks

Abstract:

"Generative Adversarial Networks - GANs - have been called the most exciting development in machine learning in a decade. You may have seen some images GANs have generated or have a high level understanding of what they are. In this talk, we'll dive deeper, describing exactly how they work - covering both their architecture and the “tricks” used to train them - what the latest advances using GANs have been, and what we can expect from them in the future."

Bios:

Seth Weidman

Seth joined Metis from Trunk Club, where he built their lead scoring models and contributed to their recommender systems. He transitioned into Data Science from management consulting by taking courses on Coursera and Udacity; this experience made him passionate about alternative education experiences such as MOOCs and bootcamps, which led him first to teach data science part time for General Assembly and ultimately led him to join Metis. Seth has Mathematics and Economics degrees from The University of Chicago.

Sponsors and Acknowledgments:

Special thanks to Rakuten hosts Pino Di Fabbrizio & Nataljia Ulemek
http://rakuten.careers (http://rakuten.careers/) for hosting this meetup

and to INTEL for providing Pizza and drinks!

Directions to Rakuten:

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