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regularization-to-avoid-overfitting

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This project explores ML techniques across classification and regression. It includes penguin species classification, breast cancer prediction, and baseball performance prediction using regularization. After, I will develop an XGBoost model for hotel cancellation prediction, analyzing key booking factors and optimizing performance. (In Progress)

  • Updated Feb 23, 2026

Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

  • Updated Sep 24, 2024
  • Jupyter Notebook

Regularization is a crucial technique in machine learning that helps to prevent overfitting. Overfitting occurs when a model becomes too complex and learns the training data so well that it fails to generalize to new, unseen data.

  • Updated Sep 8, 2024
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Pneumonia classification from chest X-ray images using a Convolutional Neural Network (CNN) built entirely from scratch layer by layer, without using any pretrained models +Canvas Tutorial presentation below for a thorough explanation and justifications for every parameter choices :

  • Updated Oct 10, 2026
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This project applies regularization techniques (Ridge, Lasso, and Elastic Net) to improve real estate price forecasting. This project focuses on reducing overfitting and increasing the stability of regression models' predictions

  • Updated Jul 1, 2025
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