Prathik Vishavadiya

Data Scientist

iNeuron•  February 2022 - March 2023

Built an Advanced House Price Prediction Project - [A I M]- Build an industry standard regression model, predict the price of a house with dataset having 81 unique features. -[ S O L U T I O N]- EDA: Gained insights into the data, quality issues, and visualized features using Matplotlib and Seaborn, including examining the distribution of the target variable and checking for missing values and outliers. Modeling approach: Handled missing values, applied log transformations, performed feature scaling, and encoded categorical features. Used algorithms with multiple perfomance metrices to evaluate the evaluate the perfomance of model Used Python libraries such as Pandas, NumPy, and Scikit-learn for data analysis and Model evaluation. Conclusion: Model achieved an accuracy of 90.04% with R2 score 0.9004