Bank Marketing
Using Python, I identified missing values, calculated descriptive statistics, analysed associations using Pearson correlation, Mann-Whitney U, and chi-square tests, and developed a machine learning model to predict whether customers will subscribe to a bank campaign.
Example of my Python code is available below.
Results from analysis
This model can be used to predict probability of customers to subscribe to campaign based on their data.
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The dashboard illustrates subscriber demographic data, including age group, marital status, education, loan status, job and number of subscribers by month.
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The dataset used for this analysis is from Moro, S., Rita, P., and Cortez, P. (2012). Bank Marketing. UCI Machine Learning Repository. https://doi.org/10.24432/C5K306.