Mel Sohm, Charles Dezons, Sami Sellami, Oscar Ninou, Axel Pincon
View original ↗Create a library that evaluates the 'distributional shift' introduced by synthetic augmentation methods before training begins. Help data scientists avoid biased synthetic training sets.
Suggested repo: augGuard
"Stop polluting your training data with biased synthetic samples."
Estimated effort: 30h