Application of Machine Learning Models to predict Credit Risk (auc = 93.64%)

Detail: Here

Conclusions:

Using Machine Learning models to forecast Credit Risk.
Matplotlib and Seaborn will be used for Data Visualization and EDA.
Best model is CatBooost.
Built prediction model with high accuracy (93.64%) to predict Credit Risk.

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Make by Lucas,

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
Forecasting Credit Risk.ipynb		Forecasting Credit Risk.ipynb
README.md		README.md
credit_risk_dataset.csv		credit_risk_dataset.csv

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