Model the price of houses using available variables so that management can understand market dynamics

• Data Cleaning includes missing value imputation, removing duplicate values, etc
• Data Preparation includes deriving metrics, converting ordinal categorical variables to label encoding and dummy variable creation
• Pre Modelling steps include train test split, normalization
• Modelling include feature elimination using RFE, p-value and VIF
• Made Linear, Ridge and Lasso Regression models and compared them by evaluating on test data