Repository files navigation Predicting Student Admissions with Neural Networks using Python π :
We tried in this notebook to predict student admissions to graduate school at UCLA based on three pieces of data.
GRE Scores (Test)
GPA Scores (Grades)
Class rank (1-4)
General overview ποΈ :
π£ Here are the steps we followed in this notebook :
Loading the data.
Plotting the data.
One-hot encoding the input variable we are interested in.
Scalling the data.
Splitting the data into Training and Testing.
Splitting the data into features and targets (labels).
Training the 1-layer Neural Network.
Calculating the Accuracy on the Test Data.
π The dataset used is provided in this repository.
π This notebook realised with the help of udacity courses .
π« Feel free to contact me if anything is wrong or if anything needs to be changed π! labrijisaad@gmail.com
About
We tried in this notebook to predict student admissions to graduate school at UCLA based on three pieces of data.
Topics
Resources
Stars
Watchers
Forks
You canβt perform that action at this time.