Interpretable Machine Learning Applications: Part 4
By Coursera
on Coursera
· Data Science
About This Course
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.
Instructor
Coursera
Frequently Asked Questions
How much does Interpretable Machine Learning Applications: Part 4 cost?
Interpretable Machine Learning Applications: Part 4 costs $9.99. Check the course page for current pricing and available discounts.
Who teaches Interpretable Machine Learning Applications: Part 4?
Interpretable Machine Learning Applications: Part 4 is taught by Coursera, Coursera.
What skill level is Interpretable Machine Learning Applications: Part 4 for?
This course is designed for all levels learners.