In real-world scenarios, over 70% of a data scientist’s time is spent cleaning and preparing raw datasets before applying machine learning models. Many students, startups, and small businesses lack the expertise to properly clean data, detect inconsistencies, and choose the right ML model. This leads to inaccurate predictions and poor decision-making.
There is a need for an intelligent system that can automatically clean datasets, detect issues, and suggest the most suitable machine learning model with explainable insights.
