House Prices - Advanced Regression Techniques

• Tech Stack: Python, Numpy, Pandas, Matplotlib, Scikit-learn, Scipy

Developed diverse regression models (Linear, Ridge, Lasso, Decision Tree, Random Forest, Gradient Boosting) for predicting real estate prices, using a detailed dataset with 79 variables in Ames, Iowa.

Employed Principal Component Analysis (PCA) for dimensionality reduction, enhancing model performance and interpretability in a complex real estate predictive analytics project.