What Is an Affinity Diagram?
February 22, 2025
Article
Recommended experience
Beginner level
Python programing experience and basic math background
Recommended experience
Beginner level
Python programing experience and basic math background
Build, Train and Test XG-Boost and Artificial Neural Networks Model
Train an ANN and XG-Boost algorithms to solve classification type problems
Perform Data Visualization and Exploratory Data Analysis
Add to your LinkedIn profile
Only available on desktop
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.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Understand the Problem Statement and Business Case
Import Libraries and Datasets
Practice Opportunity #1 [Optional]
Perform Data Visualization
Split the data into training and testing
Practice Opportunity #2 [Optional]
Build a Neural Network Model in Keras
Compile and train an ANN Model
Evaluate trained model performance
Practice Opportunity #3 [Optional]
Train and evaluate an XG-Boost Algorithm
Practice Opportunity #4 [Optional]
Python programing experience and basic math background
The Coursera Project Network is a select group of instructors who have demonstrated expertise in specific tools or skills through their industry experience or academic backgrounds in the topics of their projects. If you're interested in becoming a project instructor and creating Guided Projects to help millions of learners around the world, please apply today at teach.coursera.org.
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
Coursera Project Network
Course
University of Copenhagen
Course
University of Illinois Urbana-Champaign
Specialization
LearnQuest
Course
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
Guided Projects are not eligible for refunds. See our full refund policy.
Financial aid is not available for Guided Projects.
Auditing is not available for Guided Projects.
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.