This repository contains materials for assignments on Introduction to Machine Learning course at MIMUW in 2024.
This project combines data exploration, correlation analysis, visualization, and hypothesis testing, leading up to regression modeling of consumer behavior.
The analysis provides insights into how different factors such as income, gender, and household status relate to food expenditures and other variables.
This project explores predictive modeling on complex biological data using machine learning techniques such as ElasticNet and Random Forests.
The objective is to develop a robust model that can predict protein abundance from gene expression levels.