Admission Prediction - IBM Datathon - Group 18

Inspiration

We are currently students aiming for future studies, and we wanted to know the odds of getting admission in a university according to our scores before applying.

What it does

It takes input from the user, namely, their GRE score, TOFEL score, current CGPA, SOP, LOP and the university rating and it outputs the result according to the trained Machine Learning model.

How we built it

We used various Python libraries to build it, such as Pandas, Numpy, Seaborn and the ML Library, SciKit-Learn

Challenges we ran into

We ran into multiple challenges along the way. Our model would not output consistently.

Accomplishments that we're proud of

We're proud that the system could be used to help multiple students around the world to narrow down their list of colleges.

What we learned

Teamwork, Perseverance and Humility

What's next for Admission Prediction

We will want to improve the accuracy of the model, implement it with a front end user interface.

Built With

• matplotlib
• numpy
• pandas
• python
• scikit-learn