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Build and evaluate machine learning models to classify loan default risk using Python. Includes data preprocessing, model training, and performance metrics.

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Loan-Default-Classifier-Python

Build and evaluate machine learning models to classify loan default risk using Python. Includes data preprocessing, model training, and performance metrics.
๐Ÿ‘‰ Full annotated notebook available here: Buy on Gumroad


๐Ÿ“˜ Contents

  • Loan Default Classification Python Notebook.ipynb: The main Python notebook
  • loan_data.csv: The underlying dataset used for analysis and model training

โš™๏ธ How to Open the Notebook

To run the .ipynb file, youโ€™ll need:

  • Python 3.7+
  • Jupyter Notebook or JupyterLab

Installation Steps

  1. Go to Anaconda Download
    • Jupyter Notebook is part of Anaconda.
  2. Click Get Started
  3. Sign in using your Google account, if required.
  4. Download the installer for your operating system (Windows, Mac, or Linux).
  5. After installation, open Anaconda Navigator from your Start Menu or Applications folder.
  6. In Anaconda Navigator, click Launch under Jupyter Notebook
  7. Your browser will open with the Jupyter interface. Navigate to the file Loan Default Classification Python Notebook.ipynb and start exploring.

No additional installations needed โ€” required libraries like pandas, numpy, and scikit-learn are already included with Anaconda.


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Build and evaluate machine learning models to classify loan default risk using Python. Includes data preprocessing, model training, and performance metrics.

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