Bare bones Python implementations of some of the foundational Machine Learning models and algorithms.

Classifying the iris data without using sklearn package

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

Classification of Android applications based on playstore categories. Aim of the project is to train the logistic regression model using Training Data from App store and then predicting new application into various categories it belongs to.

linear regression python implementation