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Interpretable Machine Learning Applications: Part 4

Included with DLSEI 3.0

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

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Guided project Level

Recommended experience

2.00 Hours

Learn at your own pace

Data Science

Domain

About this guided project

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.

What skills will you gain?

Machine Learning

Artificial Intelligence and Machine Learning (AI/ML)

Statistical Modeling

Predictive Analytics

Jupyter

Data Science

Applied Machine Learning

Predictive Modeling