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Building secure machine learning environments with Amazon SageMaker



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As businesses and IT leaders look to accelerate the adoption of machine learning (ML) and artificial intelligence (AI), there is a growing need to understand how to build secure and compliant ML environments that meet enterprise requirements. One major challenge you may face is integrating ML workflows into existing IT and business work streams. A second challenge is bringing together stakeholders from business leadership, data science, engineering, risk and compliance, and cybersecurity to define the requirements and guardrails for the organization. Third, because building secure ML environments in the cloud is a relatively new topic, understanding recommended practices is also …

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