Graduate Admission Prediction with Pyspark ML
In this 1 hour long project-based course, you will learn to build a linear regression model using Pyspark ML to predict students' 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.
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- Level Intermediate
- Duration 2 hours
- Course by Coursera Project Network
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In this 1 hour long project-based course, you will learn to build a linear regression model using Pyspark ML to predict students' 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 the 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 setup and work with Pyspark on the Google Colab environment. Additionally, you will also be able to clean and prepare data for analysis. You should be familiar with the Python Programming language and you should have a theoretical understanding of Linear Regression algorithm. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.Modules
Practical Application via Rhyme
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- Graded Quiz: Test your Project understanding
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Labs
- Admission Prediction With Pyspark ML
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- Project-based Course Overview
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Dive into the world of predictive analytics with the "Graduate Admission Prediction with Pyspark ML" course. In just 1 hour, you'll master building a linear regression model using Pyspark ML to forecast university admissions. Perfect for those with Python and linear regression knowledge, this intermediate-level course is conducted on Google Colab and utilizes a Kaggle dataset for hands-on learning. Led by Coursera, it's free and ideal for North American learners, equipping you with skills in model building, data preparation, and Pyspark setup.
Priya Jha