Projects developed during the Artificial Intelligence curricular unit @ FEUP.
All code written in collaboration with Diogo Almeida and Pedro Queirós.
- Date: 2nd semester of 3rd year - 2020/2021
- Curricular unit page: IART
We chose to implement the game Neutreeko in Python.
In order to have a human-computer and computer-computer game mode, we developed an AI that runs the Minimax algorithm. The different difficulty types correspond to different variants of the algorithm (with/without alpha-beta pruning, different maximum depth).
How to run: README
Source code: Project1/src
Final presentation: Final-Slides.pdf
Final grade: 18.0/20
Our goal was to correctly label stock as buy-worthy or not. In order to accomplish it, we used the entries from the Beat US Stock market (2019 edition) data set, which contains the 10-K filings of 638 Tech Companies, to train and test our predictive model.
How to run: README
Notebook: Supervised Learning.ipynb
Final presentation: Final-Slides.pdf
Final grade: 19.0/20