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Interpretable Machine Learning Applications: Part 4
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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
Enseigné par
Epaminondas Kapetanios