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Performing classification tasks with the LibSVM toolkit on four different datasets: Iris, News, Abalone, and Income.
Plagiarism detection between documents
Sklearn-like python package with class implementations of different ML algorithms
Designed a Machine Learning model which takes newsgroup dataset and performs binary classification to predict if a given document has Atheistic or Christian sentiment. Used LIME library and PySpark. Performed feature selection to improve classifier’s performance.
Multinomial naive Bayes newsgroup document classification without relying on pre-built sklearn modules. Smoothing and inverse document frequencies utilized to improve model accuracy.