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1
Intro
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Machine Translation quality improvements
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Adaptive Machine Translation idea
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Update Example - EngFra
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Update Example: Translation Model Adaptation
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Neural MT in the Cloud
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How can we do this?
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What we had before?
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A new platform
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Architecture evolution
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Lessons Learned
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Cost efficient
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Security
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Platform high availability
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Resource allocation
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Releases are not as easy as expected
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Investigations become more complex
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Independent microservices
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Periodically reevaluate assumptions
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Future improvements
21
Demo Time!
Description:
Explore a conference talk detailing the development of a highly scalable Machine Learning platform for Machine Translation using Apache Mesos. Discover how to combine microservices architecture with Big Data technologies, including Kafka, HBase, and Hadoop, all running within a Mesos environment. Learn about the challenges faced and solutions implemented in creating this innovative platform. Gain insights into containerized microservices architecture based on Mesos, Docker, and Zookeeper. Understand the evolution of the architecture, lessons learned, and future improvements planned for this cutting-edge Machine Learning platform. Witness a demonstration of the platform's capabilities and discover how it enhances Machine Translation quality through adaptive techniques and Neural MT in the cloud.

How We Built a Highly Scalable Machine Learning Platform Using Apache Mesos

Linux Foundation
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