Machine Learning course labs and homeworks

This repo contains the labs and my 3 final evaluated homeworks for the Machine Learning course at UniPD - DEI 2021/22.

Lab 1 - Linear Regression on House Pricing Dataset

Folder: Lab1

Lab 2 - Regression on House Pricing Dataset: Variable Selection & Regularization

Folder: Lab2

Lab 3 - Linear models and Support Vector Machines

Folder: Lab3

Lab 4 - Neural Networks: Regression on House Pricing Dataset

Folder: Lab4

Homework 1 - Classification on Wine Dataset

In this notebook I work on a dataset of wines containing data for 178 instances. The dataset is the results of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars. The analysis determined the quantities of 13 constituents found in each of the three types of wines.

The goal is to perform the classification task by means of Perceptron and Logistic Regression.

Folder: HW1 | Assessment: 2.67/3

Homework 2 - SVM for classification, without and with kernels

In this notebook I am going to explore the use of Support Vector Machines (SVMs) for image classification. I am going to use the famous MNIST dataset, a dataset of handwritten digits.

Folder: HW2 | Assessment: 3/3

Homework 3 - Neural Networks for Classification, and Clustering

In the first part of this notebook I am going to explore the use of Neural Networks for image classification. I am going to use a dataset of small images of clothes and accessories, the Fashion MNIST.

In the second part, instead, I am going to cluster these images and try to understand if the clusters we obtain, by means of K-means, correspond to the true labels.

Folder: HW3 | Assessment: 3/3