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.
Diabetes Disease Detection with XG-Boost and Neural Networks
Diabetes Disease Detection with XG-Boost and Neural Networks
Instructor: Ryan Ahmed
Sponsored by InternMart, Inc
Learn, practice, and apply job-ready skills with expert guidance
Beginner level
Recommended experience
2 hours
Learn at your own pace
Hands-on learning
What you'll learn
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
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
No downloads or installation required
Only available on desktop
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About this Guided Project
Learn step-by-step
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]
Recommended experience
Python programing experience and basic math background
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Instructor
Offered by
How you'll learn
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.
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