Deep Learning Regression with Admissions Data

Brief

Objective

Overview

This project is slightly different than most on Codecademy. Instead of a step-by-step tutorial, this project contains a series of open-ended requirements that describe the project you’ll be building. There are many possible ways to fulfill all of these requirements correctly, and you should expect to use the internet, Codecademy, and other resources when you encounter a problem that you cannot easily solve.

Project Goals

For this project, you will create a deep learning regression model that predicts the likelihood that a student applying to graduate school will be accepted based on various application factors (such as test scores).

By analyzing the parameters in this graduate admissions dataset, you will use TensorFlow with Keras to create a regression model that can evaluate the chances of an applicant being admitted. You hope this will give you further insight into the graduate admissions world and improve your test prep strategy.

Setup Instructions

If you choose to do this project on your computer instead of Codecademy, you can download what you’ll need by clicking the “Download” button below. Included in the downloadable zipped folder are the admissions data and a starter code file. If you need help setting up your computer, be sure to check out our setup guide.