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Harvard vía Coursera
GRATIS

Graduate Admission Prediction with Pyspark ML

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  • Project Overview
    • In this 1 hour long project-based course, you will learn to build a linear regression model using Pyspark ML to predict student's admission at the university. We will use the graduate admission 2 data set from Kaggle. Our goal is to use a Simple Linear Regression machine learning algorithm from the Pyspark Machine learning library to predict the chances of getting admission. We will be carrying out the entire project on the Google Colab environment with the installation of Pyspark. You will need a free Gmail account to complete this project. Please be aware of the fact that the dataset and the model in this project, can not be used in the real-life. We are only using this data for learning purposes.By the end of this project, you will be able to build the linear regression model using Pyspark ML to predict admission chances. You will also be able to set up and work with Pyspark dataframes on Google colab environment. Additionally, you will also be able to clean and prepare data for analysis.