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We tried in this notebook to predict student admissions to graduate school at UCLA based on three pieces of data.

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neural-networks python jupyter-notebook one-hot-encoding

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

Predicting Student Admissions with Neural Networks using Python ๐Ÿ :

  • 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 ๐Ÿ•Š๏ธ :

  • ๐Ÿ‘ฃ 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.
  • ๐Ÿ“Š The dataset used is provided in this repository.
  • ๐Ÿ™Œ This notebook realised with the help of udacity courses.
  • ๐Ÿ“ซ Feel free to contact me if anything is wrong or if anything needs to be changed ๐Ÿ˜Ž! [email protected]

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