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SkillsCast

Microservices for Data Science and Deep Learning

7th November 2016 in London at CodeNode

There are 35 other SkillsCasts available from µCon 2016: The Microservices Conference

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Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

You will learn about using language agnostic micro services approach to handle data and provide interactive analytics in a Deep Learning / AI startup.

You will explore use cases and an example of a distributed queue based architecture for micro services.

Andrew and John will be demonstrating two different 'frameworks' for microservices in a Big Data architecture (with examples):

  1. Kafka Consumers as microservices - image processing

  2. Spark Jobs as microservices - clustering algorithms + data visualisation

Andrew and John will also share their experiences of using microservices at Tractable.

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Thanks to our sponsors

Microservices for Data Science and Deep Learning

John Bradshaw

John is studying for a PhD at the University of Cambridge and the Max Planck Institute for Intelligent Systems, Tübingen in Machine Learning. Prior to that he worked as an engineer at Tractable implementing scalable Machine Learning algorithms.

Andrew Jefferson

Andrew is a software engineer specialising in realtime data systems. Andrew has worked at YC Startups and at Apple on applications ranging from Ticketing to Genetics. Currently building data systems for training and exploiting Deep Neural Networks for Computer Vision.

SkillsCast

Please log in to watch this conference skillscast.

Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

You will learn about using language agnostic micro services approach to handle data and provide interactive analytics in a Deep Learning / AI startup.

You will explore use cases and an example of a distributed queue based architecture for micro services.

Andrew and John will be demonstrating two different 'frameworks' for microservices in a Big Data architecture (with examples):

  1. Kafka Consumers as microservices - image processing

  2. Spark Jobs as microservices - clustering algorithms + data visualisation

Andrew and John will also share their experiences of using microservices at Tractable.

YOU MAY ALSO LIKE:

Thanks to our sponsors

About the Speakers

Microservices for Data Science and Deep Learning

John Bradshaw

John is studying for a PhD at the University of Cambridge and the Max Planck Institute for Intelligent Systems, Tübingen in Machine Learning. Prior to that he worked as an engineer at Tractable implementing scalable Machine Learning algorithms.

Andrew Jefferson

Andrew is a software engineer specialising in realtime data systems. Andrew has worked at YC Startups and at Apple on applications ranging from Ticketing to Genetics. Currently building data systems for training and exploiting Deep Neural Networks for Computer Vision.

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