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Production Challenges Unveiled

Companies often face significant hurdles when transitioning machine learning models from development to production. A common issue is the gap between a model built on a local machine and its deployment in a live environment, particularly for teams lacking machine learning expertise. Once deployed, understanding the model's behavior in production presents another layer of complexity, as monitoring these models differs greatly from traditional software services.