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。
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Responsible AI for Developers: Interpretability & Transparency - 日本語版
Instructor: Google Cloud Training
Included with
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
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July 2024
1 assignment
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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
Instructor
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.