This repo contains the main files related to the first homework of the course "Artificial Intelligence and Machine Learning" at Politecnico di Torino; I'm publishing this, and will do the same for the next two ones, so to give something like a guideline to who ever will have to do something similar in the future and doesn't have any clue where to start from or anyway has any doubt.
The purpose of this homework was to let us experience Principal Component Analysis as a dimesionality reduction method and as a image compression (and reconstruction) method, plus to experience the use of a Naive Bayes Classifier.
A dataset of images composed of House, Dog, Guitar and Person labels was provided and the code was developed ad hoc for this dataset, however i will not provide such a dataset. Further details on the implementation are provided in the WriteUp.
Enjoy!