[Table 1] Graduate Admissions Success Predictor (GASP)

Inspiration

Everyone in the team is interested in machine learning and getting into grad school. This led us to develop a machine learning algorithm that we could potentially use to predict our own grad school admissions.

What it does

We found it fascinating that we could potentially predict the probability of getting into graduate school based on several factors. The user inputs their data, based on which our algorithm outputs a probability.

How I built it

We coded multivariable linear regression from scratch on Python using the numpy library and then used JavaScript to build our website.

Challenges I ran into

We faced a very steep learning curve with both machine learning and web development. Normalizing our data was very important to obtain stable results, which we initially did not implement.

Accomplishments that I'm proud of

The fact that our project was successfully completed was very satisfying.

Built With

Submitted to

Hack on the Hill 6
- Winner Best Machine Learning Project

Created by

I worked on implementing the machine learning algorithm to determine the probability of getting into graduate school.

varunsiva33
I worked on implementing the machine learning algorithm in numpy, as well as the output functions for the web app.

andyshen55
I worked on the frontend and helped import and clean the data.

Prajakta Ranade
I helped build our machine learning algorithm for the graduate school admissions chance predictions. I also contributed to the javaScript code for taking user inputs and applying the weights from the AI algorithm.

Vaishnavi Tipireddy
Siddarth Chalasani