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loan-default-prediction

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Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discrete variables using various techniques depending on the feature. Checked for missing values and cleaned the data. Built the probability of default model using Logistic Regression. Visualized all the results. Com…

  • Updated Mar 31, 2020
  • Jupyter Notebook
Home-Credit-Default-Risk-Recognition

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

  • Updated Jul 1, 2020
  • Jupyter Notebook

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