Fault detection in steel plates using different machine learning models.
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Updated
Jul 8, 2025 - Jupyter Notebook
Fault detection in steel plates using different machine learning models.
Implementation of various algorithms on scikit-learn's Toy Datasets.
Academic Machine Learning projects using Python, including Adaboost, ANN, Naive Bayes, and more
Predict forest cover types using Random Forest and XGBoost on the Covertype dataset.
WinQ leverages machine learning to predict wine quality using key physicochemical features, delivering actionable insights with strong model accuracy. Developed for Stanford Code in Place 2025, this project showcases the power of Python and data science fundamentals in a real-world context.
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