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Building a successful ML project & Surrogate modelling

Feb 11, 2019 · London, United Kingdom

Welcome to the 3rd London Applied Deep Learning Meetup!

Building a successful ML project - Tom Nicholson
Machine learning is hot, and everyone wants in, from researchers, to engineers and CEOs. This collision of worlds yields a situation that has new and interesting problems of coordination, collaboration, and execution. In this talk we’ll investigate how we can set up machine learning projects to succeed, and how we all can contribute to push ML out of the lab, through industry, and into people’s lives.

Tom has worked in a number of machine learning focused startups across mobile, finance and blockchain. He has experience across the R&D spectrum from original research to delivery. He trained originally as a computer scientist, and holds a masters in machine learning from Cambridge.

Surrogate modelling: The next deep learning frontier? - Raza Habib
Raza will argue that surrogate modelling is a huge and under-appreciated opportunity for machine learning and deep learning in particular. We'll discuss when and when not to use deep learning in practice and why surrogate modelling is particularly well suited to deep learning.

Raza Habib is a PhD student at UCL supervised by David Barber, where he studies the intersection between probabilistic machine learning and Deep Learning. He is also an advisor to Monolith AI, where he helps apply machine learning to accelerate engineering design.

Plan:
-- 7:30pm Doors Open
-- 7:45pm Tom Nicholson
-- 8:15pm Break
-- 8:30pm Raza Habib
-- 9:00pm Finish

Event organizers
  • Applied Deep Learning Meetup

    Everyone is talking about Deep Learning nowadays, but when will we see in-the-wild applications of GANs? Will Deep Reinforcement Learning ever be used in an industrial setting, other than optimising power usage in Google data centers? Who will have the best hardware implementations of quantized neural net chips? In this group, we aim to find answers (or paths towards those answers) for those vague questions, and more. Stay tuned!

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