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Azure Machine Learning (AML) helps customers achieve 'fast time to solution' by leveraging best in class algorithms, cloud compute, storage and deployment. Deploying a robust and scalable end-to-end AML solution requires a good strategy for building automated data pipelines to call trained machine learning models for scoring and to move data, such as, scoring features and predicted outcome from these models. This webinar, covers common use-case driven strategies, architectures and the tools needed to build automated data pipelines for consuming trained AML models. The first half will be presentation content and the second will be open Q&A for everyone interested in optimizing their machine learning solutions.
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