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Boston Housing Analysis
Project type
Machine Learning Model
This project analyzes the Boston Housing Dataset, which contains 506 entries with 14 attributes related to housing prices in different Boston suburbs. The analysis explores key factors such as crime rate, property tax, room count, and accessibility to highways, influencing median home values. Various statistical techniques and visualizations were applied using Python, Pandas, Seaborn, and Matplotlib to uncover trends and insights.
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