College Admission

Machine Learning Discovery

In this project, I wanted to create a model to predict if a high school student will be admitted into college based on elements provided in my dataset like GPA, GRE, and Rank.
This project has a challenge which is a small dataset so I try to deal with the challenge using different methods to create the prediction model.
Also, I implement the project in both R and Python.

What done in this project?

• EDA
  

• Clean dataset.
  

• Organize dataset columns types.
  

• Provide a chart to understand data.
  

• Work on predict catagorical value yes/no and try 3 different model on it.
  

• Machine Learning Models:
  

  • Logistic Regression
    
  • GBM
    
  • Random Forest
    
  • Extra:KNN
    

NOTE: I used green color for plots I know it's not suitable because of Color blindness but I chose it because it's the color of my college KKU. I used different Color Saturation to solve this problem.

Repository content

• College_Admission in R
  
• College_Admission in Python
  
• College_Admission_Report Markdown