While implementing retraining on a set cadence is easier, dynamic retraining can prevent models from becoming outdated and optimize computational costs.
Read it!In a data science project, certain values such as file names, train-test split ratios, and hyperparameters often undergo frequent changes. By using configuration files instead of hard-coding these values, you can achieve better maintainability and flexibility.
Read it!How Dynamic Meter, the New York Times ML model that sets personalized meter limits and makes the paywall smarter, works.
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