ml-r

Code for ML course

Implemented models:

• naive Bayes model fot spam classification
• principal component analysis, using Gram-Schmidt process and iterative QR-method
• k-means algorithm using expectation maximization and gradient descent methods; ; k-means using gradient descent over Davies–Bouldin index
• implementation of linear regression with gradient descent and normal equations; implementation of logistic regression with gradient descent