In this 1-hour long guided project, you will learn how to use the "What-If" Tool (WIT) in the context of training and testing machine learning prediction models. In particular, you will learn a) how to set up a machine learning application in Python by using interactive Python notebook(s) on Google's Colab(oratory) environment, a.k.a. "zero configuration" environment, b) import and prepare the data, c) train and test classifiers as prediction models, d) analyze the behavior of the trained prediction models by using WIT for specific data points (individual basis), e) moving on to the analysis of the behavior of the trained prediction models by using WIT global basis, i.e., all test data considered.
Interpretable Machine Learning Applications: Part 4
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4.7
(10 reviews)
Intermediate level
Recommended experience
1.5 hours
Learn at your own pace
Hands-on learning
What you'll learn
Set up a machine learning application in a "zero configuration" environment such as Google's Colab(oratory) Research platform.
Set up and configure the What-If Tool to analyze the behavior of exemplary machine learning prediction models.
Skills you'll practice
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:
Set up the environment for the "What-If" tool (WIT) as an extension in Jupyter and as a Google's Colaboratory notebook, including importing of the dataset (e.g., white wine quality data)
Train classifiers, e.g., Decision Tree and Random Forest, as exemplary machine learning prediction models to make predictions about the quality of white wines.
Launch the What-If Tool (WIT) widget. This task will allow us to get a first understanding on how our prediction model(s) behave at both individual and global levels.
Use the What-If Tool (WIT) features to explain the behavior of a prediction model on an individual basis.
Use the What-If Tool (WIT) advanced features to explain the behavior of a prediction model on an individual basis.
Use the What-If Tool (WIT) features to explain the behavior of a prediction model on a global basis.
Recommended experience
Some basic knowledge on machine learning, statistics and data science.
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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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Frequently asked questions
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.