This repository contains the assignment which involves building a regression model using regularization techniques to predict the actual value of prospective properties for Surprise Housing, a US-based company looking to enter the Australian market.
Surprise Housing utilizes data analytics to purchase houses below their actual values and sell them at a higher price. For their expansion into the Australian market, they have collected a dataset from house sales in Australia. The goal is to build a regression model that predicts the actual value of prospective properties and aids in decision-making regarding investments.
Identify significant variables in predicting house prices. Assess how well these variables describe house prices. Determine the optimal value of lambda for ridge and lasso regression.
The dataset used for analysis is provided in a CSV file. It contains information about various aspects of houses in Australia, including features like size, location, amenities, etc.