Advance_Housing_Price_Regression

This project aims to perform advance regression using regularization method like Ridge regression and Lasso regression.

Table of Contents

General Information

  • A US-based housing company has decided to enter the Australian market, They have collected a sales data and before entering the market they want to perform the data analysis.
  • The company is looking for prospective properties to buy in australia before entering the market.
  • Here we are trying to understand the pricing dynamics of new market and help firm to manuplate its strategy to yield high returns.
  • Here Housing dataset of Australia is being used, Data set contains 70 variables.

Conclusions

  • Here in this project we performed the Linear Regression, Ridge Regression and Lasso Regression. After perfoming all the three Regression process. We can conclude that Ridge regression is able to generalize model well as R2 score difference for train and test data is less compared to other two.
  • Important features are present in the Notebook at the end.

Technologies Used

  • pandas - version 1.5.3
  • numpy - version 1.22.4
  • seaborn - version 0.12.2
  • matplotlib - version 3.7.1
  • sci-kit learn - version 1.2.2

Acknowledgements

Give credit here.

  • This project is inspired by my dreams and aspiration

Contact

Created by Harshit-tech9 - feel free to contact me at harshitpanchalcie16@gmail.com