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