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insurance-claims

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Predicting insurance premiums using machine learning algorithms. It involves analyzing various factors such as age, medical history, lifestyle, and coverage details to estimate the cost of insurance for individuals or groups.

  • Updated May 6, 2024
  • Jupyter Notebook

Sure Tomorrow used machine learning to tackle challenges. I assessed its efforts to identify clients for marketing, forecast the chance of new client claims, and ensure better predictive performance, all while safeguarding client privacy without affecting previous models.

  • Updated Aug 7, 2023
  • Jupyter Notebook

This repository features code for the Allstate Claims Severity Kaggle competition, utilizing Python, primarily XGBoost, and LightGBM for predicting insurance claim losses. Through preprocessing and hyperparameter tuning, LightGBM attains the best validation MAE of 0.4157, selected for test dataset predictions and competition submission.

  • Updated May 14, 2023
  • Jupyter Notebook

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