This repository contains my data analytics and machine learning result from the Graduate Admission 2 dataset. ( ⭐️ Star repo on GitHub — it helps! )
University admissions can be confusing and stressful. Most of the times, in order to know the status of admission it can take up a lot of time.
This repo mainly focuses on what parameters are important for a student to get into post graduate college. By the end of this repo it will be clear of what are the scores required for different tests to have better admission chances and get into a dream masters program?
An ipython notebook is used for data preprocessing, trend analysis and data visualiation. All core scripts are in file .ipynb" folder. All result output are in result folder and the detailed description of the data can be found in Kaggle.
- Rohit Kumar Singh
- Ranjith Kumar Govindarajan
Feel free to send us feedback on file an issue. Feature requests are always welcome. If you wish to contribute, please take a quick look at this kaggle.
Written with StackEdit.