Machine Learning

This repository contains all the assignments and the project I did for the Machine Learning course at the School of Applied Mathematics of the Getulio Vargas Foundation (FGV EMAp). The course was taught by Professor Diego Mesquita.

Assignments

1. Nearest Neighbours Method ($k$-NN) (10/10)
2. Linear Regression (8.5/10)
3. Logistic Regression and Approximate Bayesian Inference (10/10)
4. Selection of Models and Hyperparameters (9.25/10)
5. Gaussian Processes for Regression (10/10)
6. Neural Networks (10/10)
7. Dimensionality Reduction (10/10)
8. K-means and Mixture models (8.5/10)

Final Project

The final project was co-authored by Ana Carolina Erthal, Guilherme de Melo and Bernardo Vargas. The project implements a way of comparing Conformal Prediction with traditional machine learning approaches to generate confidence intervals.