18 reactions · 22 shares | MLOps is a set of practices and tools for streamlining the deployment, maintenance, and management of ML models in a production environment. The goal of MLOps is to ensure that models are reliable, secure, and scalable, while also making it easier for data scientists and engineers to develop, test, and deploy ML models. Read more: https://hubs.la/Q02fGY810 #mlops #machinelearningops | Data Science Dojo | Facebook
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FacebookData Science Dojo
18 reactions · 22 shares | MLOps is a set of practices and tools for streamlining the deployment, maintenance, and management of ML models in a production environment. The
Data Science Dojo. . MLOps is a set of practices and tools for streamlining the deployment, maintenance, and management of ML models in a production environment. The goal of MLOps is to ensure that models are reliable, secure, and scalable, while also making it easier for data scientists and engineers to develop, test, and deploy ML models ...
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MLOps Best Practices
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Demetrios Brinkmann speaks to Jon Krohn about the meaning and tasks of MLOps, how to build and run an online community, and the best tools for scaling LLMs. Watch the full episode: https://bit.ly/sdsp787 Thank you to Amazon Web Services (AWS) for supporting this episode of SuperDataScience, enabling the show to be freely available on all major podcasting platforms and on YouTube. #datascience #mlops #mlopscommunity | Superdatascience
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