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