Opensource ML Frameworks on Amazon SageMaker (Level 300)
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Amazon Web Services766 тыс
Следующее
04.04.19 – 55340:18Популярные
3 дня – 7801:57
Опубликовано 4 апреля 2019, 17:51
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Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly. Amazon SageMaker automatically configures and optimizes TensorFlow, Apache MXNet, Chainer, PyTorch, Scikit-learn, and SparkML so you do not have to do any setup to start using these frameworks. In this session, we look at how to use these frameworks with Amazon SageMaker and enable seamless movement of workloads between Amazon SageMaker and your infrastructure.
Speaker: Aparna Elangovan, Solutions Architect, AWS, ANZ
Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly. Amazon SageMaker automatically configures and optimizes TensorFlow, Apache MXNet, Chainer, PyTorch, Scikit-learn, and SparkML so you do not have to do any setup to start using these frameworks. In this session, we look at how to use these frameworks with Amazon SageMaker and enable seamless movement of workloads between Amazon SageMaker and your infrastructure.
Speaker: Aparna Elangovan, Solutions Architect, AWS, ANZ
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