This repository contains the homeworks for the AIML course at the Politecnico di Torino in 2019-20.
They deal with the following topics:

1. Shallow learning analysis of the Wine dataset using Sklearn
2. Deep learning image classification using the Caltech101 dataset
3. Domain adaptation in the PACS dataset

Each folder contains the source code as .py or .pynb file as well as a subfolder "report", where you can read along how the analysis was carried out both in pdf format and in the original tex format.