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Facilitating the Spread of Knowledge and Innovation in Professional Software Development

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Neural Networks across Space and Time

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Summary

Dave Snowdon starts with a brief introduction to deep neural networks, why they are important and how they work. He covers two of the most important deep neural architectures: convolutional networks which excel at handling images, and recurrent networks which handle time-series or sequential input. He shows examples of both convolutional and recurrent networks using the deeplearning4j framework.

Bio

Dave Snowdon is a programmer working on cloud management of virtual desktop infrastructure (VDI) at VMware. He wrote a system to generate unique pieces of music for each user based on information extracted from audio, rhythms and images supplied by the user. More recently, he has been devoting his time to understanding ML with a particular emphasis on deep neural networks.

About the conference

Software is changing the world. QCon empowers software development by facilitating the spread of knowledge and innovation in the developer community. A practitioner-driven conference, QCon is designed for technical team leads, architects, engineering directors, and project managers who influence innovation in their teams.

Recorded at:

Jun 29, 2018

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