A Repository for all the assigned assignments by Assistant Professor Shashadhar Das, Dept CSE, BVEC
Fault detection in steel plates using different machine learning models.
Early-stage thyroid cancer detection using supervised ML with SMOTE class balancing on UCI clinical dataset.
Academic Machine Learning projects using Python, including Adaboost, ANN, Naive Bayes, and more
Implementation of various algorithms on scikit-learn's Toy Datasets.
A Statistical Framework for Scoring and Monitoring Scientific Datasets
Technical working paper on optimizing the weighted nearest neighbors (wNN) regression algorithm by learning feature-specific distance metric weights via batch gradient descent, achieving up to 80.65% MSE reduction over conventional wNN on UCI benchmarks.
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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