Master Explainable AI: Interpreting Image Classifier Decisions

Master Explainable AI: Interpreting Image Classifier Decisions

Discover Explainable AI tools to interpret deep learning image classifiers. Lead the GenAI revolution by implementing and evaluating saliency maps, class activation maps, and interpretability metrics. Future-proof your skills.

Advanced

34 Lessons

7h

Certificate of Completion

Discover Explainable AI tools to interpret deep learning image classifiers. Lead the GenAI revolution by implementing and evaluating saliency maps, class activation maps, and interpretability metrics. Future-proof your skills.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Project
1 Assessment
30 Playgrounds
5 Quizzes

This course includes

1 Project
1 Assessment
30 Playgrounds
5 Quizzes

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

What You'll Learn

A deep understanding of the need and benefits of Explainable AI

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Course Content

1.

Introduction to Explainable AI

Get familiar with Explainable AI to understand and implement transparent, interpretable AI systems.
3.

Class Activation Maps

Work your way through Class Activation Maps, GradCAM, X-GradCAM, Eigen-CAM, and Ablation-CAM techniques.
4.

Miscellaneous Methods

Apply your skills to various advanced methods for interpreting AI image classifiers.
5.

Metrics of Interpretability

Dig into interpretability metrics for AI, feature agreement, rank correlation, predictive faithfulness, and fairness.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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