https://github.com/eduribeiro00/covidforecast-feup-iart
Code and projects developed in the IART subject throughout the semester (MIEIC 3rd year, 2nd semester).
https://github.com/eduribeiro00/covidforecast-feup-iart
ai machine-learning python regression-models sklearn
Last synced: about 2 months ago
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Code and projects developed in the IART subject throughout the semester (MIEIC 3rd year, 2nd semester).
- Host: GitHub
- URL: https://github.com/eduribeiro00/covidforecast-feup-iart
- Owner: EduRibeiro00
- Created: 2020-02-18T10:01:11.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-10-03T12:18:04.000Z (over 4 years ago)
- Last Synced: 2025-01-29T17:11:56.991Z (4 months ago)
- Topics: ai, machine-learning, python, regression-models, sklearn
- Language: Jupyter Notebook
- Homepage:
- Size: 46.4 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# IART Class Assignments and Projects
**2019/2020** - 3rd Year, 2nd Semester
**Course:** Inteligência Artificial ([IART](https://sigarra.up.pt/feup/pt/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=436449)) | Artificial Intelligence
**Projects developed by:** Eduardo Ribeiro ([EduRibeiro00](https://github.com/EduRibeiro00)), José Guerra ([LockDownPT](https://github.com/lockdownpt)) and Miguel Pinto ([MiguelDelPinto](https://github.com/MiguelDelPinto))
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**Project 1: Neutron**
* Neutron is a board game normally played on a 5 x 5 board. The goal of each player is to bring the Neutron to their home rank (the first rank on their side of the board), or to stalemate the other player. The full game rules can be found here: https://boardgamegeek.com/boardgame/6978/neutron
* Developed a full game with menu, difficulty selection, visual interface, etc. Allows Human v Human, Human vs Computer and Computer vs Computer, on 5x5, 7x7 and 11x11 boards;
* Developed various levels of AI using the Minimax algorithm and implemented optimizations like Alpha-Beta pruning;
* Languages/technologies used: **Python.**
**Grade**: 19.5 / 20
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**Project 2: Covid Forecast Tool**
* Extracted Covid-19 data from a Kaggle dataset that contained the confirmed, death, and recovered cases for each day and for each country/region; developed and trained several regression models with the goal of successfully predicting Covid-19 cases and deaths;
* Used data visualization Python libraries to create graphs in order to better understand data patterns;
* Utilized the following models and methods: Neural Networks, Stochastic Gradient Descent, Support Vector Machines, K-Nearest Neighbours and Random Forest.
* Kaggle dataset used: https://www.kaggle.com/imdevskp/corona-virus-report?select=covid_19_clean_complete.csv
* Languages/technologies used: **Python, Jupyter Notebook, SKLearn, Pandas, Numpy, Matplotlib, Seaborn.**
**Grade**: 18.0 / 20
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**Disclaimer** - This repository was used for educational purposes and I do not take any responsibility for anything related to its content. You are free to use any code or algorithm you find, but do so at your own risk.