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Responsible AI for Developers: Interpretability & Transparency

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Это упражнение является частью курса

Responsible AI for Developers: Interpretability & Transparency

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This module introduces the course structure and objectives.

Exercise 1: Course Introduction

This module focuses on AI interpretability and transparency. It provides various techniques and tools to help achieve interpretability and transparency in both data and AI models.

Exercise 1: Overview of interpretability and transparency Exercise 2: Overview of interpretability techniques Exercise 3: Feature based explanations: Model agnostic Exercise 4: Feature based explanations: Model specific Exercise 5: Concept-based and example-based explanations Exercise 6: Tools for interpretability Exercise 7: Data and Model Transparency Exercise 8: Lab: Vertex Explainable AI Exercise 9: Explaining an Image Classification Model with Agent Platform Explainable AI Exercise 10: AI Interpretability & Transparency Question 1 Exercise 11: AI Interpretability & Transparency Question 2 Exercise 12: AI Interpretability & Transparency Question 3

This module provides a summary of the entire course by covering the most important concepts, tools, and technologies.

Exercise 1: Course Summary Exercise 2: Reading

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Exercise 1: Course Resources