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34 Lessons
7h
Certificate of Completion
Learn about popular Explainable AI algorithms such as integrated gradient, LIME, class activation maps, counterfactual explanations, etc.
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This course includes
This course includes
Course Overview
Explainable AI is a set of tools and frameworks that helps you understand and interpret the internal logic behind the predictions made by a deep learning network. With this, you can generate insights into the behavior and working of the model to mitigate issues around it in the development phase. In this course, you will be introduced to popular Explainable AI algorithms such as smooth gradient, integrated gradient, LIME, class activation maps, counterfactual explanations, feature attributions, etc., for i...Show More
What You'll Learn
A deep understanding of the need and benefits of Explainable AI
The ability to design and implement popular explanation algorithms
Hands-on experience combining existing explanation methods to generate more robust explanations
An understanding of explainers used to interpret the decision of a neural network
The ability to evaluate and quantify the quality of the neural network explanations
Course Content
Introduction to Explainable AI
Saliency Maps
Class Activation Maps
Miscellaneous Methods
Metrics of Interpretability
Final Assessment
Assessment
Weakly Supervised Object Localization
Project
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