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Name: Flying Phase
Type: Organization
Bio: Advanced analytics thru machine learning
Blog: www.flyingphase.com
Name: Flying Phase
Type: Organization
Bio: Advanced analytics thru machine learning
Blog: www.flyingphase.com
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
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.
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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