This repository contains my solutions to the assignments of the autumn 2016 version of the Stanford university course CS229: Machine Learning.

For more information about CS229 visit: http://cs229.stanford.edu/

Content:

Problem Set 1

LogisticRegressionWithNewton.py: an implementation of logistic regression using Newton's method to fit the parameters.

Regression.py: an implementation of linear and weighted linear regression using the normal equations to calculate the parameters.

ProblemSet2:

naivebayes.py/naivebayes.ipynb: spam classification using a own implementation of the naive bayes algorithm and a svm with linear kernel from scikit-learn.