- 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)
- 👣 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.
- 📊 The dataset used is provided in this repository.
- 🙌 This notebook realised with the help of udacity courses.
- 📫 Feel free to contact me if anything is wrong or if anything needs to be changed 😎! labrijisaad@gmail.com
