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This study aims to analyze a Book Club's customer data to predict response to a new book offering and optimize marketing strategy using data mining techniques.
German Credit dataset was utilized to evaluate the creditworthiness of loan applicants, allowing financial institutions to make informed decisions. This project used machine learning techniques, including logistic regression, classification trees, and neural networks, to predict credit risk and maximize net profit.
This project employs predictive analytics and data mining techniques to optimize a company's mailing strategy for its new catalog. By developing a binary classification model to predict the likelihood of purchase and a regression model for estimating spending among purchasers, the analysis enables the company to target potential customers more effectively, ultimately increasing the gross profit generated from the catalog mailings."