Machine-Learning Rock Paper Scissors

Python application with a graphical user interface where the player face a bot at Rock Paper Scissors.

Link to project:

How It's Made:

Tech used: Python, xgboost, tkinter

The GUI was built using tkinter. The bot that you play against can draw on simple strategies such as markov chains to machine learning-based approaches including decision trees and gradient boosting. The models were trained using data from approximately 250,000 games on roshambo.me.

Lessons Learned:

This was my first experience creating a program with a graphical user interface. I also leveraged OOP to a greater extent than my previous projects to create the interface. It was also fun to train the machine learning models and apply them to a live game that considers historical inputs rather than as a static predictor.

Installing:

This repo has not been packaged into a .exe. To install, clone the repository and execute python rps_gui.py.