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
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.
Artificial Neural Network
Python Programming
Machine Learning
Deep Learning
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]
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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.
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