Most ML issues are not model problems. They are data problems.I retrained the same churn model twice.Same code. Same path to the data.Different result.Why? Because of mutable data references. I wrote a small Data Lake vs Data Lakehouse demo showing why versioned data makes ML debugging reproducible: https://tinyurl.com/lake-vs-lakehouse-medium Friend-Link: https://medium.com/towards-artificial-intelligence/from-data-lake-to-data-lakehouse-why-ai-changes-the-rules-for-data-platforms-c78feab48e1c?sk=405811cbc10baa4622bcfcad90736ed4#ai #machinelearning #data #lakehouse #warehouse #python #datalake #technology #regression
