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supervised-learning-classifiers

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A comprehensive collection of Machine Learning algorithms from beginner to advanced, featuring mathematical foundations, Python implementations, model training, optimization, evaluation techniques, and practical examples using Scikit-learn and other ML libraries.

  • Updated Nov 13, 2026
  • Jupyter Notebook

Predicting customer retention in an e-commerce platform using classification models. Includes data preprocessing, feature engineering, and model evaluation (Logistic Regression, SVM, Random Forest, KNN, Decision Tree). Best model achieves 83% accuracy and perfect recall. Ideal for business use.

  • Updated Apr 1, 2025
  • Jupyter Notebook

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