Microservices for Data Science and Deep Learning
Please log in to watch this conference skillscast.
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):
Kafka Consumers as microservices - image processing
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:
- Software Architecture for Developers Workshop with Robert Smallshire (in London on 9th - 10th September 2019)
- Lightbend Scala Language - Professional (in London on 9th - 10th September 2019)
- ProgNET London 2019 (in London on 11th - 13th September 2019)
- CloudNative London 2019 (in London on 25th - 27th September 2019)
- Ethics in Artificial Intelligence (in London on 23rd July 2019)
- Keynote by Emily Jiang on On Stage Hacking: Build 12-Factor Microservices in an Hour (in London on 23rd July 2019)
- Django London Meetup (SkillsCast recorded in July 2019)
- A Machine That Predicts the Global Economy in Real-Time (SkillsCast recorded in July 2019)
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.
Please log in to watch this conference skillscast.
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):
Kafka Consumers as microservices - image processing
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:
- Software Architecture for Developers Workshop with Robert Smallshire (in London on 9th - 10th September 2019)
- Lightbend Scala Language - Professional (in London on 9th - 10th September 2019)
- ProgNET London 2019 (in London on 11th - 13th September 2019)
- CloudNative London 2019 (in London on 25th - 27th September 2019)
- Ethics in Artificial Intelligence (in London on 23rd July 2019)
- Keynote by Emily Jiang on On Stage Hacking: Build 12-Factor Microservices in an Hour (in London on 23rd July 2019)
- Django London Meetup (SkillsCast recorded in July 2019)
- A Machine That Predicts the Global Economy in Real-Time (SkillsCast recorded in July 2019)
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.