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Accelerating recommendation system development with Azure Machine Learning

%3CLINGO-SUB%20id%3D%22lingo-sub-865387%22%20slang%3D%22en-US%22%3EAccelerating%20recommendation%20system%20development%20with%20Azure%20Machine%20Learning%3C%2FLINGO-SUB%3E%3CLINGO-BODY%20id%3D%22lingo-body-865387%22%20slang%3D%22en-US%22%3EThe%20Microsoft%2FRecommenders%20repository%20is%20a%20publicly%20available%20set%20of%20tools%20and%20best%20practices%20to%20help%20developers%20and%20data%20scientists%20build%20recommender%20systems.%20This%20session%20provides%20a%20quick%20introduction%20on%20the%20types%20of%20recommendation%20systems%20and%20approaches%20for%20building%20them%2C%20then%20dives%20into%20the%20repository%2C%20explaining%20the%20components%20that%20can%20be%20used%20to%20accelerate%20the%20development%20of%20recommendation%20engines.%20Learn%20how%20Azure%20ML%20makes%20it%20easy%20to%20train%20models%2C%20optimize%20hyperparameters%2C%20organize%20multiple%20experiments%2C%20and%20deploy%20recommendation%20services%20into%20production%20systems.%3C%2FLINGO-BODY%3E%3CLINGO-LABS%20id%3D%22lingo-labs-865387%22%20slang%3D%22en-US%22%3E%3CLINGO-LABEL%3EWRK3018%3C%2FLINGO-LABEL%3E%3C%2FLINGO-LABS%3E
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Community Manager
The Microsoft/Recommenders repository is a publicly available set of tools and best practices to help developers and data scientists build recommender systems. This session provides a quick introduction on the types of recommendation systems and approaches for building them, then dives into the repository, explaining the components that can be used to accelerate the development of recommendation engines. Learn how Azure ML makes it easy to train models, optimize hyperparameters, organize multiple experiments, and deploy recommendation services into production systems.

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