swarnava-96 / college-graduate-admission-prediction

Predicting graduate admissions from an Indian perspective.

College-Graduate-Admission-Prediction

Goal: The goal of this project is to predict Graduate Admissions from an Indian perspective.

About the data set:

The data set is downloaded from Kaggle. The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are :

1. GRE Scores ( out of 340 )
2. TOEFL Scores ( out of 120 )
3. University Rating ( out of 5 )
4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 )
5. Undergraduate GPA ( out of 10 )
6. Research Experience ( either 0 or 1 )
7. Chance of Admit ( ranging from 0 to 1 )

Project Description:

1. After loading the data set, data pre-processing was performed. Data pre-processing steps included, checking for null values, removing unwanted features, feature scaling, dividing into independent and dependent features and finally train test split.

2. Then, a two layer neural network ANN model was built from scratch for this regression problem statement and trained for 10 epochs. I have tried multiple models just to increase the performance of the model. Model was evaluated on the basis of R2 score. Finally, a plot showing loss vs validation loss was plotted as shown below:

Kaggle Kernel: https://www.kaggle.com/swarnavamukherjee/college-graduate-admission-using-ann