Questions tagged [mlops]
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Which tool do you use for creating continuous training pipelines for MLOPS?
One key component of MLOPS is continuous training. Which means the end to end training is put in a pipeline which can be triggered, versioned and metadata of the pipeline can be tracked. Thus enabling ...
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How to deal with errors or inconsistencies in the training data?
There are inconsistant wrong labels and consistant errors in training data. For the former I tried MC-dropout and data Shapley. For the later I wonder if manual data curation is a requisite?
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How do I verify and test a machine learning model against reality during time?
As a software engineers we familiar with a concept of testing (unit, integration, e2e) Tests give us a level of confidence about the code and changes in our code.
Looks like for ML the "code"...
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Manually labeled data quality check methods?
In this article, the author says that manual data labeling is a "not-as-bad-as-it-sounds" method, but to err is human and in this article by Shopify, I learned that high-quality annotation ...
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Is my idea of a Feature Store wrong?
Cross-posted on Reddit ML.
Should a Feature Store be part of an enterprise data catalog?
To me, a feature store seems to be a highly niche data catalog but missing a lot of the benefits of having an ...
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What features used by CNN model should a feature store actually store? [closed]
According to MLOPs principle, it is recommended to have a feature store. The question is in the context of doing image classification using deep learning models like convolutional neural networks ...
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MLflow real world experience
Can someone provide a summary of the real world deployment experience of MLflow? We have a few ML models (e.g., LightGBM, tensorflow v2, etc.) and want to avoid framework like SageMaker (due to ...
