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Optimize Amazon SageMaker deployment strategies

April 19, 2022
High-performance and cost-effective model deployment strategies help maximize your organisation's ML investments. Learn about different deployment options and strategies using Amazon SageMaker, including optimized infrastructure choices; real-time, asynchronous, and batch inferences; multi-container endpoints; multi-model endpoints; auto scaling; model monitoring; and CI/CD integration for your ML workloads. Discover how to choose a better inference option for your ML use case, and hear from Docebo about how they leverage Amazon SageMaker and AWS AI services for fast, low-latency, and scalable ML deployment.
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