Performing classification tasks with the LibSVM toolkit on four different datasets: Iris, News, Abalone, and Income.

Sklearn-like python package with class implementations of different ML algorithms

Plagiarism detection between documents

Multinomial naive Bayes newsgroup document classification without relying on pre-built sklearn modules. Smoothing and inverse document frequencies utilized to improve model accuracy.

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.