このコースでは、AI の解釈可能性と透明性のコンセプトを紹介します。デベロッパーとエンジニアにとって AI の透明性が重要であることについて説明します。データと AI モデルの両方で解釈可能性と透明性を達成できる実践的な方法とツールを検証します。
Responsible AI for Developers: Interpretability & Transparency - 日本語版
Responsible AI for Developers: Interpretability & Transparency - 日本語版
Instructor: Google Cloud Training
Sponsored by Louisiana Workforce Commission
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
AI に関連する解釈可能性と透明性を定義する
AI における解釈可能性と透明性の重要性を説明する
AI における解釈可能性と透明性を達成するために使用されるツールと手法を確認する
Details to know
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Assessments
1 assignment
Taught in Japanese
Recently updated!
July 2024
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There are 4 modules in this course
What's included
1 video
このモジュールでは、AI の解釈可能性と透明性に焦点を合わせます。データと AI モデルの両方で解釈可能性と透明性を達成できるさまざまな手法やツールを紹介します。
What's included
9 videos1 assignment1 app item
このモジュールでは、最も重要なコンセプト、ツール、テクノロジーについて取り上げ、コース全体の概要を説明します。
What's included
1 video1 reading
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What's included
3 readings
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