Data Analysis

Machine Learning on Federal Student Loan Repayment

With the background of the global pandemic and economic recession, the outstanding amount of federal student loan has reached an all-time high. In this project, we'll conduct a machine learning exploration of factors contributing to the repayment rate of federal student loan, use several different machine learning algorithms and compare their performance in this task. We hope this can help us find how machine learning can tell us the story behind rather complex datasets and provide insights for real-world problems.

Bank’s Debt Collecting Analysis

After a debt has been legally declared "uncollectable" by a bank, it does not walks away from the debt. They still want to collect some of the money they are owed. The bank will implement different levels of debt collecting strategies, advanced collecting strategies, of course, cost more money.

In this project, we'll load the banking dataset and try to inspect regression discontinuity to answer the question: whether it's worth the extra cost spending on debt collecting for the bank?

Mobile Games Operation A/B Testing

In mobile games design, we want to get users' retention, which means potential profits. In this project, we'll load one of the mobile games' users dataset and conduct A/B tesing, to find out which one of the two different level designs attracts the players more.

Credit Card Approvals Prediction

Commercial banks receive a lot of credit card applications, and manually analyze these applications could be error-prone and time-consuming. In this project, we'll utilize machine learning techniques to perform a supervised learning with scikit-learn, try to automate the credit card approving process.