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Using supervised machine learning to train a model with credit default data to determine the probability and/or classification (“default” vs “non-default”) of the user’s liability. The UI will take user input such as, such as education level, sex, marital status, payment history and income, and will return a classification.
An app like this would be useful for financial and lending institutions to understand and manage the risk of their loans and lending portfolios.
- Determining probability of user liability
- Creating an interactive UI that will take users input and return an output
- To determine if a neural network vs logistic regression is the better model for classification
- Logistic Regression
- Random Forest Model
- Deep Neural Network
Probability of Credit Card Default, Machine Learning
Technologies Used : -