Building Serverless Machine Learning Workflows (Level 300)
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Amazon Web Services776 тыс
Следующее
03.04.19 – 11 32922:37Популярные
Опубликовано 3 апреля 2019, 17:43
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Modern machine learning workflows leverage AWS services, such as Amazon Transcribe and Amazon Comprehend, to extract, validate, mutate, and enrich your data. Some might drive transactional systems that use machine learning to generate metadata for media assets, while others might derive insights by visualizing customer interaction sentiment from call logs. They all share a common challenge, orchestrating a combination of distinct sequential and parallel steps that are fulfilled by independent microservices. Join us as we examine how workflows can be used to manage that orchestration in a way that is scalable, reliable, and easy to maintain and run, and also how to perform CI/CD for machine learning model training and deployment with AWS Step Functions.
Speaker: Donnie Prakoso, Technology Evangelist, AWS, ASEAN
Modern machine learning workflows leverage AWS services, such as Amazon Transcribe and Amazon Comprehend, to extract, validate, mutate, and enrich your data. Some might drive transactional systems that use machine learning to generate metadata for media assets, while others might derive insights by visualizing customer interaction sentiment from call logs. They all share a common challenge, orchestrating a combination of distinct sequential and parallel steps that are fulfilled by independent microservices. Join us as we examine how workflows can be used to manage that orchestration in a way that is scalable, reliable, and easy to maintain and run, and also how to perform CI/CD for machine learning model training and deployment with AWS Step Functions.
Speaker: Donnie Prakoso, Technology Evangelist, AWS, ASEAN
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