Interpretable Machine Learning Applications: Part 4

Übersicht

Interpretable Machine Learning Applications:

Part 4

Join this 1-hour guided project to explore the 'What-If' Tool (WIT) in the context of training and testing machine learning prediction models. You'll gain hands-on experience in:

• Setting up a machine learning application using Python in an interactive notebook on Google's Colaboratory environment.
• Importing and preparing data.
• Training and testing classifiers as prediction models.
• Utilizing WIT to analyze the behavior of trained prediction models for specific data points on an individual basis.
• Extending the analysis to a global basis, considering all test data.

Enhance your understanding of machine learning models with practical tools and insights.

University:

Provider:

Coursera

Categories:

Python Courses, Machine Learning Courses, Data Visualization Courses

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Unterrichtet von

Epaminondas Kapetanios

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Fachgebiete