Graduate Admission Analysis

• Tech Stack: Tensorflow, Python, numpy, keras, pandas
• Github URL: Project Link

Conducted EDA on a dataset containing 400K rows along with numerous input variables such as GRE, TOEFL, CGPA, etc

Predicted the chance of an admit using Linear Regression, Random Forest, KNN, Neural Networks algorithms.

Applied Ensembling: Logistic Regression & KNN with Averaging methods to achieve better performance

Performed data transformation followed by calculation of correlation between the variables