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Addressing Model Staleness in Machine Learning Pipelines

Model reliability in machine learning involves not only performance but also factors such as data and environment, latency, and speed of the model. Three important types of tests for model reliability are unit tests, integration tests, and smoke tests. Model staleness occurs when a model's performance decreases over time due to changes in data or the environment.

Question: Which of the following actions can help address model staleness? (Select all that apply)

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Developing Machine Learning Models for Production

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