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Valohai vs. SageMaker

Which data science challenges do these two machine learning platforms solve? Download the whitepaper now!

What's inside?

Machine learning platforms take many forms and usually solve only one or a few parts of the ML problem space. In this whitepaper we introduce the problem space and look at a detailed comparison between Valohai and AWS SageMaker.
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Data management

Both platforms are built for both structured and unstructured data in, stored e.g. in Amazon S3, but where SageMaker has features for labeling and data visualization, Valohai focuses on data traceability. Valohai automatically builds a data dictionary of all input and output data helping organizations govern models, data and their trace.
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Model development

Where SageMaker is built for Python and AWS, Valohai runs any programming language and framework on top of any cloud provider or on-premises hardware. Valohai is also agnostic in terms of the development environment your data scientists use.
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Prediction serving

SageMaker integrates with AWS IAM for role based access where Valohai supports several various authentication methods. In terms of technical serving, Valohai let’s you deploy to a Kubernetes cluster without knowledge about how to set up a cluster yourself.

Read the full comparison of Valohai and SageMaker
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