So i am basically a student doing Bachelors in AI i am currently in my 4th semester and participate in a lot of kaggle competitions
The main problem that i face in these competitions is data cleaning, for larger datasets that exceeds 80 mb it takes about 2-3 hours of cleaning therefore to solve this problem i have been making a ML preprocessor that cleans your dataset and make them ML ready for any algorithm depending on your selections such as XGBoost , Regression, and etc
Currently i am almost done and will soon be deploying this
Would love to hear your thoughts on this idea is it really a problem or am i overthinking it