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learning-material

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🍾 A comprehensive machine learning project using Random Forest algorithm to predict wine quality based on physicochemical properties. Features EDA, model training, hyperparameter tuning, feature importance analysis, and detailed documentation.

  • Updated Jul 26, 2025
  • Jupyter Notebook

🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient dataset with 13 medical features. Complete ML pipeline from data exploration to model evaluation.

  • Updated Jul 25, 2025
  • Jupyter Notebook

🚗 Predict car prices instantly with Linear & Lasso Regression! Built with Streamlit, scikit-learn, pandas & matplotlib. Compare models, explore data, and learn ML hands-on. Fast, open source, and easy to use for students & developers!

  • Updated Jul 26, 2025
  • Jupyter Notebook

🚀 Complete ML Project: Salary Prediction using Linear Regression & Streamlit. 95.6% accuracy, interactive web interface, clean dataset, pre-trained model. Perfect for learning ML, web development, and practical HR applications.

  • Updated Jul 26, 2025
  • Jupyter Notebook

👨 K-Means Clustering Customer Segmentation is an interactive Streamlit app that uses machine learning to group customers by income and spending habits. It helps businesses target marketing, personalize offers, and gain insights with easy retraining, visualizations, and modular code.

  • Updated Jul 26, 2025
  • Jupyter Notebook

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