Episode 46: why do machine learning models fail? (Part 2)
Sep 4th, 2018 by datascienceathome
In this episode I continue the conversation from the previous one, about failing machine learning models.
When data scientists have access to the distributions of training and testing datasets it becomes relatively easy to assess if a model will perform equally on both datasets. What happens with private datasets, where no access to the data can be granted?
At fitchain we might have an answer to this fundamental problem.