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Responsible AI for Developers
Interpretability & Transparency - 简体中文
Google Cloud Training
Google Cloud Training
本课程介绍了 AI 可解释性和透明度的相关概念，探讨了 AI 透明度对于开发者和工程师的重要性。同时探索了有助于在数据和 AI 模型中实现可解释性和透明度的实用方法及工具。
Register for this course and see more details by visiting:
OpenCourser.com/course/s3ro71/responsible
What's inside
Syllabus
课程简介
本单元介绍课程结构和目标。
AI 可解释性和透明度
本单元着重介绍 AI 可解释性和透明度，还介绍了有助于在数据和 AI 模型中实现可解释性和透明度的各种方法和工具。
Read more
Syllabus
课程简介
本单元介绍课程结构和目标。
AI 可解释性和透明度
本单元着重介绍 AI 可解释性和透明度，还介绍了有助于在数据和 AI 模型中实现可解释性和透明度的各种方法和工具。
Read more
课程总结
本单元对整个课程进行总结，回顾最重要的概念、工具和方法。
课程资源
所有单元的学员 PDF 链接
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
探討 AI 可解釋性對於開發者和工程師的重要性。
涵蓋從基礎到進階的 AI 可解釋性概念。
授課單位為 Google Cloud Training，具備業界認可。
提供實用方法與工具，提升資料和 AI 模型的可解釋性和透明度。
課程架構清楚，包含課程簡介、概念介紹和課程總結，方便學習。
課程資料豐富，提供每個單元的 PDF 連結，方便查閱。
Save this course
Save Responsible AI for Developers: Interpretability & Transparency - 简体中文 to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Responsible AI for Developers: Interpretability & Transparency - 简体中文 with these
activities:
Compile Notes and Create Cheat Sheets
Show steps
Organize notes and create cheat sheets can help improve memorization, enhance critical thinking, and improve problem-solving skills.
Show steps
-
Organize your notes from the course
-
Create cheat sheets based on the most important concepts
Complete AI Transparency Tutorial by Open AI
Show steps
Open AI's tutorial provides comprehensive guide to help understand and implement practical AI Transparency techniques.
Show steps
-
Register for Open AI's tutorial
-
Complete the video tutorials
-
Attempt the quizzes and exercises
Practice Interpret Machine Learning Models
Show steps
Practicing interpreting machine learning models trains your mind to recognize patterns and improve your understanding of how they work.
Show steps
-
Find a dataset that you are interested in
-
Choose a machine learning model to use (e.g., logistic regression, decision tree, etc.)
-
Train the model on the dataset using your chosen model
-
Interpret the model's output using visualizations or explanations
Two other activities
Expand to see all activities and additional details
Show all five activities
Create a Presentation on AI Transparency Best Practices
Show steps
Creating a presentation forces you to synthesize your knowledge and develop a strong understanding of the material.
Show steps
-
Research AI transparency best practices
-
Create a presentation outline
-
Develop the presentation slides
-
Practice the presentation
Join Coursera AI Enthusiasts Discussion Group
Show steps
Talking with your peers helps to build confidence, clarify concepts, and build your network.
Show steps
-
Search for relevant discussion groups on Coursera
-
Join the discussion group
-
Participate in discussions
Compile Notes and Create Cheat Sheets
Show steps
Organize notes and create cheat sheets can help improve memorization, enhance critical thinking, and improve problem-solving skills.
Show steps
Show steps
Show steps
- Organize your notes from the course
- Create cheat sheets based on the most important concepts
Complete AI Transparency Tutorial by Open AI
Show steps
Open AI's tutorial provides comprehensive guide to help understand and implement practical AI Transparency techniques.
Show steps
Show steps
Show steps
- Register for Open AI's tutorial
- Complete the video tutorials
- Attempt the quizzes and exercises
Practice Interpret Machine Learning Models
Show steps
Practicing interpreting machine learning models trains your mind to recognize patterns and improve your understanding of how they work.
Show steps
Show steps
Show steps
- Find a dataset that you are interested in
- Choose a machine learning model to use (e.g., logistic regression, decision tree, etc.)
- Train the model on the dataset using your chosen model
- Interpret the model's output using visualizations or explanations
Two other activities
Expand to see all activities and additional details
Show all five activities
Create a Presentation on AI Transparency Best Practices
Show steps
Creating a presentation forces you to synthesize your knowledge and develop a strong understanding of the material.
Show steps
Show steps
Show steps
- Research AI transparency best practices
- Create a presentation outline
- Develop the presentation slides
- Practice the presentation
Join Coursera AI Enthusiasts Discussion Group
Show steps
Talking with your peers helps to build confidence, clarify concepts, and build your network.
Show steps
Show steps
Show steps
- Search for relevant discussion groups on Coursera
- Join the discussion group
- Participate in discussions
Career center
Learners who complete Responsible AI for Developers: Interpretability & Transparency - 简体中文 will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/s3ro71/responsible
Reading list
We haven't picked any books for this reading list yet.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/s3ro71/responsible
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Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
August 12, 2024
- September 16, 2024
Language
zh-CN
Good to know
探討 AI 可解釋性對於開發者和工程師的重要性。
涵蓋從基礎到進階的 AI 可解釋性概念。
授課單位為 Google Cloud Training，具備業界認可。
提供實用方法與工具，提升資料和 AI 模型的可解釋性和透明度。
課程架構清楚，包含課程簡介、概念介紹和課程總結，方便學習。
課程資料豐富，提供每個單元的 PDF 連結，方便查閱。
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