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
Access provided by Abu Dhabi National Oil Company
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
3 hours to complete
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
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
1 assignment
Taught in Japanese
See how employees at top companies are mastering in-demand skills
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
すべてのモジュールへの受講者用 PDF リンク
What's included
3 readings
Instructor
Offered by
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