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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