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Wednesday, March 03, 2021

Retrain Your Model, Update the Data

Such an obvious thing, but often forgotten. I make a point to include such updating instructions in everything I delivered.   No data, except from physics, is static.  Estimate, at least, the risk involved in not updating a model consistently.    It also applies to all analytical models, beyond AI/ML models.  We did it in common optimization models in the enterprise.  

Why is re-training ML Models Important?

A Product Manager’s Perspective  in Towards Data Science

By Humberto Corona (totó pampín)

As a product manager, you are responsible for measuring the continuous success of your product. That might include validation before launching, measuring uplifts in an A/B test while launching, and keeping track of core KPIs. If you are managing a Machine Learning product, the long-term success of your product will depend on keeping your models up-to-date. In this post I explain why this is important problem and how can you ensure that continuous success through model re-training.  ... "

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