This deals with EDA and building various ML models using sklearn: KNeighborsRegressor DecisionTreeRegressor RandomForestRegressor,AdaBoostRegressor LinearRegression, Ridge,Lasso CatBoostRegressor XGBRegressor
And performing HP using RandomizedSearchCV
Developed Flask based mini web app to access the model and re-use for prediction