Kobe Bryant Shot Prediction Project

Overview

This is a project done for the Machine Learning course at the Faculty of Mathematics, University of Belgrade.

Project Goals

The goal of the project is to compare various machine learning algorithms for binary classification. Specifically, it aims to evaluate their accuracy in predicting whether Kobe Bryant took a shot under certain circumstances.

Algorithms used

• Logistic Regression
• K-Nearest Neighbors (KNN)
• Decision trees
• Random forests
• Support Vector Classification (SVC)
• XGBoost
• Ada Boost
• Neural Networks