This project aims to analyze and predict graduate admission chances for students applying to top colleges abroad. The analysis focuses on understanding the important factors in graduate admissions and how these factors interrelate. This tool estimates the chances of admission from an Indian perspective.

Objective

The objective of this analysis is to:

Identify the key factors influencing graduate admissions.
Understand the interrelationship among these factors.
Predict one's chances of admission based on the identified variables.

Features

Probability Estimation: Estimates the chances of admission to Ivy League colleges based on various factors.
Data Analysis: Provides insights into the key factors influencing admissions.
Predictive Modeling: Uses machine learning algorithms to predict admission probabilities.

Dataset

The dataset includes the following columns:

GRE Score: The applicant's GRE score (out of 340).
TOEFL Score: The applicant's TOEFL score (out of 120).
University Rating: Rating of the university (out of 5).
Statement of Purpose (SOP): Strength of the SOP (out of 5).
Letter of Recommendation (LOR): Strength of the LOR (out of 5).
CGPA: Undergraduate CGPA (out of 10).
Research Experience: Whether the applicant has research experience (1: Yes, 0: No).
Chance of Admit: Probability of admission (0 to 1).

Methodology

Data Cleaning: Handling missing values and outliers.
Exploratory Data Analysis (EDA): Visualizing the relationships between different variables.
Feature Engineering: Creating new features and selecting the most relevant ones.
Model Building: Training various machine learning models to predict admission chances.
Model Evaluation: Evaluating the performance of the models using metrics like accuracy, precision, recall, and F1-score.

Results

The analysis identified the following factors as the most significant in predicting graduate admissions:

GRE Score
TOEFL Score
University Rating
SOP Strength
LOR Strength
CGPA
Research Experience

The predictive model achieved an accuracy of X% (replace X with your result). Usage

To use this project, follow these steps:

Clone the repository:

bash

git clone https://github.com/lm934/Case-Study-Graduate-Admission-Predictor.git

Conclusion

This project provides a comprehensive analysis of the factors influencing graduate admissions and offers a tool to predict admission probabilities. It can be further enhanced by incorporating more features and data.