APARTMENT SALES IN BUENOS AIRES

Heathcliff Nyambiya

Econometrician | Data Scienctist | Financial Engineering Candidate

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About this project

For each assessment, students must score 90%. Learners build a linear regression model to predict apartment prices in Argentina. They create a data pipeline to impute missing values and encode categorical features, and they improve model performance by reducing overfitting. -Loaded multiple CSV files into a Pandas DataFrame -Cleaned messy data with a wrangle function -Created a machine learning pipeline with feature encoding and imputation -Created insightful visualizations like a Mapbox scatter plot, a heatmap, and a bar chart for model coefficients

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