/JSW_Internship

Property Prediction model using regression algorithms , this project is the part of my summer internship at JSW steel 2021 We were provided with raw data of 5135 rows and 45 columns which had to be cleaned first and later applied 5 different algorithms like KNN, Random Forest, ANN, Support Vector Regressor and Multiple Regressor to predict which gave the highest R2_score value and the least RMSE. Conclusion :- Random Forest was found to be relatively the best learner for this model and hence we deployed our machine learning model using html, css, flask.

Primary LanguageJupyter NotebookMIT LicenseMIT

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