This project analyzes the Boston Housing dataset using a linear regression algorithm. The methodology involves the use of quantitative secondary data to ensure proper data analysis. The project focuses on applying linear regression to the Boston Housing dataset, a standard benchmark for regression analysis. The student uses the linear regression algorithm to analyze the dataset and its components. The project references several academic papers on data cleaning, regression modeling, and data mining techniques. The goal is to provide a practical application of linear regression to a real-world dataset, demonstrating the ability to manage and interpret the results of the analysis. The project aims to enhance understanding of data analysis, regression techniques, and the management of project analysis.
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