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Flying Phase's Projects

bfsi_credx_capstone icon bfsi_credx_capstone

CredX is a leading credit card provider that gets thousands of credit card applications every year. But in the past few years, it has experienced an increase in credit loss. The CEO believes that the best strategy to mitigate credit risk is to ‘acquire the right customers’. In this project, your task is to help CredX identify the right customers using predictive models. Using past data of the bank’s applicants, you need to determine the factors affecting credit risk, create strategies to mitigate the acquisition risk and assess the financial benefit of your project

dataweek-workshop icon dataweek-workshop

Machine learning workshop using Python, pandas, and scikit-learn. The first half of the day covered supervised classification using Logistic Regression and how to use cross validation to evaluate your models . The second half of the day covered unsupervised clustering with Kmeans as well as an overview of the data science process.

project-_-home-credit-default-risk icon project-_-home-credit-default-risk

Using Machine Learning to identify default risk on loans given out by Home Credit (Kaggle Competition - 2019). Models, including Random Forests and XGBoost had AUC ROC of .775.

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