Active Learning on Kubernetes and Amazon SageMaker
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70 дней – 7415:15Опубликовано 7 августа 2019, 18:42
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The process of automating workflows with machine learning models often requires a significant amount of labeled data. Acquiring this data can be a costly and time consuming process. Active learning is a type of machine learning that reduces the amount of labeled data required by allowing the model to select which examples will be labeled. In this talk, we describe the challenges and solutions Alkymi has encountered while implementing active learning on AWS using Kubernetes and SageMaker.
The process of automating workflows with machine learning models often requires a significant amount of labeled data. Acquiring this data can be a costly and time consuming process. Active learning is a type of machine learning that reduces the amount of labeled data required by allowing the model to select which examples will be labeled. In this talk, we describe the challenges and solutions Alkymi has encountered while implementing active learning on AWS using Kubernetes and SageMaker.
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