US based housing company Surprise Housing wants invest in Australian Market. They are planning to purchase houses at a price below their actual values and flip them on at a higher price.
This project is aimed at building ML regression model using regularization to predict the actual values of properties in Australia, so the company can decide wheather to invest or not.
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Provide general information about your project here. This project is aimed at building a different variants of ML model using regularization and selecting the best model that predicts the actual values of properties in Australia.
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What is the background of your project? This is an Advanced Regression assignment taken as a part of AI&ML Jan 2024 batch IIIT-Bangalore
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What is the business probem that your project is trying to solve? ML regression model is built to predict the actual value of the properties in Australia.
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What is the dataset that is being used? The train.csv dataset is being used to build the model. The dataset includes various attributes describing houses in Australia along with the target variable, the sale price.
- Neighborhood, Sale Condition, LotShape, MSSubClass, KitchenAbvGr, 1st and 2nd Floor square feet, LandContour, Exterior1st are some of the important features that decides the property prices in Australia
- pandas library - version 2.0.3
- numpy library - version 1.24.3
- matplotlib library - version 3.7.2
- seaborn library - version 0.12.2
- statsmodels library - version 0.14.0
- sklearn library - version 1.3.0
Give credit here.
- This Linear Regression assignment was taken as a part of AIML - Jan 2024 batch IIIT-Bangalore
Created by [@smarunkumar] - feel free to contact me!