Machine Learning

Description

This project was made for the Machine Learning course at the AGH UST in 2024/2025. All solutions are results of my work after hours, when I was solving given tasks (topics).

Exercises and Topics

1. Interpretability of ML models - Shapley method (SHAP)

2. Interpretability of ML models - Lime

3. Bayesian methods

4. Time series 1

5. Time series 2

6. Generative models

7. Restricted Boltzmann Machines and Deep Belief Networks

Technology stack

• Python