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predicting-student-admissions-with-neural-networks-using-python's Introduction

Predicting Student Admissions with Neural Networks using Python 🐍 :

  • 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 🕊️ :

  • 👣 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 😎! [email protected]

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