Surprise Housing, a US-based company specializing in data-driven house flipping, is entering the Australian market. This assignment focuses on building a regression model to predict house prices and assess investment potential.
- Objective: This project aims to equip Surprise Housing with predictive insights to optimize house purchases in the Australian market, maximizing profitability through accurate pricing strategies.
- Significance: By identifying key variables influencing house prices, the project enhances decision-making capabilities, ensuring informed investments.
- Python: 3.12.2
- Jupyter Notebook: 7.4.2
- Anaconda: 2023.10
- Libraries:
- Numpy: 1.26.2
- Pandas: 2.1.4
- Plotly: 5.18.0
- Matplotlib: 3.6.2
- Seaborn: 0.12.2
- Statsmodels: 0.14.0
- Scikit-learn (Sklearn): 1.2.0
- Identify Significant Variables: Determine features with statistically significant impacts on house prices using regression analysis.
- Model Accuracy Assessment: Evaluate the predictive performance of linear, polynomial, ridge, and lasso regression models.
- Optimize Regularization Parameters: Fine-tune lambda parameters for ridge and lasso models to achieve optimal predictive power.
- Data Preparation: Cleaned and prepared the
train.csv
dataset provided by UpGrad, ensuring data integrity and consistency. - Visualization: Visualized data patterns and insights to understand relationships between variables.
- Model Building:
- Utilized Recursive Feature Elimination (RFE) to select relevant features for linear regression.
- Applied polynomial regression (degree 2) and addressed overfitting with ridge and lasso regression techniques.
- Model Validation: Conducted residual analysis to validate model assumptions and ensure robustness across training and test datasets.
- Data Preparation: Ensured dataset cleanliness and preparedness for accurate modeling.
- Model Performance: Developed robust regression models (linear, polynomial, ridge, lasso) validated through rigorous analysis.
- Insights: Derived actionable insights into Australian housing market dynamics, enabling strategic decision-making for Surprise Housing.
- Resources: Leveraged resources from:
Created by @SandeepGitGuy - Feel free to reach out!