Logistic Regression Model for University Admissions

Project Overview

This project is a Python implementation of a logistic regression model to predict a student's probability of admission to a university based on their scores from two exams. It demonstrates the fundamental components of a machine learning classification model, built from scratch using NumPy.

The model learns a decision boundary from historical data to classify new applicants as either "Admitted" or "Not Admitted."

How to Run

1. Clone this repository to your local machine.
2. Navigate into the university-admissions-model directory.
3. Create and activate a Python virtual environment:

   python3 -m venv .venv
   source .venv/bin/activate