Diabetes Disease Detection with XG-Boost and Neural Networks
In this project-based course, we will build, train and test a machine learning model to detect diabetes with XG-boost and Artificial Neural Networks. The objective of this project is to predict whether a patient has diabetes or not based on their given features and diagnostic measurements such as number of pregnancies, insulin levels, Body mass index, age and blood pressure.
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- Level Beginner
- Duration 2 hours
- Course by Coursera Project Network
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In this project-based course, we will build, train and test a machine learning model to detect diabetes with XG-boost and Artificial Neural Networks. The objective of this project is to predict whether a patient has diabetes or not based on their given features and diagnostic measurements such as number of pregnancies, insulin levels, Body mass index, age and blood pressure.Modules
Your Learning Journey
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- Assess Your Knowledge
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- Diabetes Disease Detection with XG-Boost and Neural Networks
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- Project Overview
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Discover how to detect diabetes using XG-Boost and Neural Networks in this beginner-friendly, project-based course by Coursera. Over 120 minutes, you'll build, train, and test a machine learning model, predicting diabetes based on features like pregnancies, insulin levels, BMI, age, and blood pressure. Perfect for those looking to delve into personal development and machine learning, and it's free to subscribe!
Ryan Ahmed