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Manage your end-to-end machine learning lifecycle with MLOps

%3CLINGO-SUB%20id%3D%22lingo-sub-866110%22%20slang%3D%22en-US%22%3EManage%20your%20end-to-end%20machine%20learning%20lifecycle%20with%20MLOps%3C%2FLINGO-SUB%3E%3CLINGO-BODY%20id%3D%22lingo-body-866110%22%20slang%3D%22en-US%22%3EMLOps%20is%20all%20about%20helping%20you%20bring%20your%20machine%20learning%20workflows%20to%20production.%20This%20session%20shows%20you%20how%20to%20get%20to%20production%20faster%20with%20optimized%20experiences%20for%20model%20training%2C%20packaging%2C%20validation%2C%20deployment%20and%20monitoring%20-%20and%20automate%20%2B%20audit%20all%20of%20this%20within%20your%20existing%20DevOps%20tooling.%20With%20ML%20Ops%20you%20can%20store%20and%20version%20models%20in%20production%2C%20collect%20continuous%20feedback%20on%20model%20behavior%2C%20and%20maintain%20quality%20models%20to%20keep%20your%20business%20and%20customers%20ahead.%20Target%20audience%20for%20this%20session%20includes%20data%20engineering%2C%20data%20science%20and%20AppDev%20personas.%3C%2FLINGO-BODY%3E%3CLINGO-LABS%20id%3D%22lingo-labs-866110%22%20slang%3D%22en-US%22%3E%3CLINGO-LABEL%3EBRK3035%3C%2FLINGO-LABEL%3E%3C%2FLINGO-LABS%3E
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Community Manager
MLOps is all about helping you bring your machine learning workflows to production. This session shows you how to get to production faster with optimized experiences for model training, packaging, validation, deployment and monitoring - and automate + audit all of this within your existing DevOps tooling. With ML Ops you can store and version models in production, collect continuous feedback on model behavior, and maintain quality models to keep your business and customers ahead. Target audience for this session includes data engineering, data science and AppDev personas.

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