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PANEL DISCUSSION

Panel: The Purpose of Machine Learning

In the machine learning world, there is no shortage of buzzwords. Each trend follows the next in rapid succession, during the panel we will discuss how and when our panelists decide to pick up on a trend and when to focus on proven technology. We delve into these decisions based on their definition of success and company goals.

During the session, we hope to find promising trends to pick up on and to pinpoint the similarities and differences between a data scientist and a software engineer in terms of achieving business value.


Speaker

Thomas van Heyningen

Data Science Consultant at NAVARA

Thomas is an enthusiastic and practical data scientist. He is always finding ways to integrate data science into business processes. Approaching each use case with a fresh sense of curiosity, figuring out the process and problem at hand. Working as a data science consultant in The Netherlands,...

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Speaker

Nicholas Mitchell

Machine Learning Engineer at @argoai

Nicholas is a Machine Learning Engineer at Argo AI, solving the task of perception for autonomous vehicles. He is also a part-time researcher, completing a Ph.D. in cross-domain applications of AI.

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Speaker

Jendrik Jördening

CTO @Nooxit

Jendrik is CTO at Nooxit. He formerly worked at Aurubis and Akka Germany on Data Science and Deep Learning in the field of industry 4.0 and autonomous machines.At the same time he took part in the Udacity Self-Driving Car Nanodegree, participating with a group of other Udacity student in the...

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Speaker

Diana Hu

Startup Advisor and former CTO for Escher Reality

Diana currently is advising startups and angel investing. Previously she was the head of the AR platform at Niantic. She led the AR teams building the core AR tech used in games like Pokemon Go and Harry Potter Wizards Unite. Previously, she was the Cofounder and CTO of Escher Reality, a...

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