Distributed deep learning and why you may not need it - Jakub Sanojca, Mikuláš Zelinka

PyData Warsaw 2018 Deep learning thrives with always bigger networks and always growing datasets but single machine can only handle so much. When to scale to multiple machines and how do do it efficiently? What pros and cons available options have and what is theory behind their approach to distributed training? In this talk we will answer those questions and show what problems we are trying to solve at Avast. === PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organizat