The challenging pursuit of developing and productionizing ML models can be supported and automated through MLOps, a specialization of the DevOps paradigm from software development. Therefore, MLOps offers significant potential for DS projects, which are suffering from notable failure rates.
MLOps is a git-based open-source project. This platform includes MLReef11, which provides a centralised location for managing the ML development process. This ...
The challenge in executing a data science project is more than just identifying the best algorithm and tool set to use. Additional sociotechnical challenges ...
Aug 19, 2023 · The significance of the Machine Learning Operations (MLOps) methods, which can provide acceptable answers for such problems, is examined in this study.
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Oct 3, 2024 · looking for real world MLOps project ideas · pull some data for training, train initial model · create preprocessing pipeline with tests · setup CI ...
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Dec 8, 2023 · MLOps is needed pretty much everywhere. By building something that I care about, I will be more consistent in my endeavors.
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Feb 1, 2023 · In summary, if we want to have successful machine learning projects under our belt, we need to learn the science of MLOps. To do this, we ...
Sep 25, 2024 · MLOps (Machine Learning Operations) is a set of practices for collaboration and communication between data scientists and operations professionals.
Aug 11, 2023 · MLOps aims to streamline the time and resources it takes to run data science models using automation, ML and iterative improvements on each ...
This manuscript presents an open-source Machine Learning Operations (MLOps) Template that provides a consistent framework to support collaborative development ...