Diabetes Prediction With Pyspark MLLIB
In this 1 hour long project-based course, you will learn to build a logistic regression model using Pyspark MLLIB to classify patients as either diabetic or non-diabetic. We will use the popular Pima Indian Diabetes data set. Our goal is to use a simple logistic regression classifier from the pyspark Machine learning library for diabetes classification. 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 3 hours
- Course by Coursera Project Network
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In this 1 hour long project-based course, you will learn to build a logistic regression model using Pyspark MLLIB to classify patients as either diabetic or non-diabetic. We will use the popular Pima Indian Diabetes data set. Our goal is to use a simple logistic regression classifier from the pyspark Machine learning library for diabetes classification. 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 educational purpose. By the end of this project, you will be able to build the logistic regression classifier using Pyspark MLlib to classify between the diabetic and nondiabetic patients.You will also be able to setup and work with Pyspark on 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 the Logistic Regression algorithm. You will need a free Gmail account to complete this project. 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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Assignment
- Graded Quiz: Test your Project understanding
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Labs
- Diabetes Prediction With Pyspark MLLIB
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- Project-based Course Overview
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Unlock the potential of PySpark MLlib with our engaging project-based course, "Diabetes Prediction With PySpark MLlib". Designed for data science and AI enthusiasts, this intermediate-level course spans 1 hour and delves into building a logistic regression model to classify patients as diabetic or non-diabetic using the renowned Pima Indian Diabetes dataset. Guided by Coursera's expert instructors, you will embark on this educational journey through the Google Colab environment, learning to set up and utilize PySpark effectively. The hands-on experience focuses on data cleaning, preparation, and applying a logistic regression classifier using PySpark MLlib. Ideal for those with a foundational understanding of Python and logistic regression, this course requires a free Gmail account for full participation. While the dataset and model used are for educational purposes only, the skills and knowledge gained will be invaluable for your data science toolkit. Join now for free and elevate your data science capabilities in just 180 minutes. Note: The course currently offers the best experience for learners in North America, with plans to expand globally. Don't miss out on this opportunity to enhance your data science expertise with practical, project-based learning.
Priya Jha