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🏦 Scoring credit application

OPENCLASSROOMS - Data Scientist - Project 7

This repository contains files to build, run and deploy a machine learning web application which predicts the probabiliy for a customer to repay a loan.

📊 Data

The dataset used for this project is the Home Credit Default Risk, which includes information on hundreds of thousands loans.

📁 Project Organization


├── LICENSE
├── README.md
│
├── api                <- FastAPI files
│
├── dashboard          <- Streamlit application
│
├── data
│   ├── external       <- Data from third party sources (not uploaded on git)
│   ├── processed      <- Data after analysis and feature engineering
│
├── docs               <- Documentation and reports
│
├── mlruns             <- MLFlow runs   
│
├── models             <- Trained and serialized models
│
├── notebooks          <- Jupyter notebooks
│
├── tests              <- Pytest unit tests (local)

🛠️ Tools

  • Python 3.x
  • Jupyter Notebook
  • NumPy
  • Pandas
  • Matplotlib / Seaborn
  • Scikit-learn
  • Imbalanced-learn
  • XGBoost
  • LightGBM
  • Hyperopt
  • SHAP
  • Evidently
  • MLFlow
  • Streamlit
  • FastAPI
  • Docker
  • GitHub Actions
  • Azure Web App

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OPENCLASSROOMS - Formation Data Scientist - P7

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