本課程第二部分著重在和人工智慧密不可分的機器學習。課程內容包含了機器學習基礎理論(包含 1990 年代發展的VC理論)、分類器(包含決策樹及支援向量機)、神經網路(包含深度學習)及增強式學習(包含深度增強式學習。
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人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)
National Taiwan UniversityAbout this Course
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Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 11 hours to complete
Chinese (Traditional)
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 11 hours to complete
Chinese (Traditional)
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Syllabus - What you will learn from this course
2 hours to complete
Concept learning
2 hours to complete
6 videos (Total 73 min), 2 readings, 1 quiz
2 hours to complete
Computational Learning Theory
2 hours to complete
8 videos (Total 120 min)
2 hours to complete
Classification
2 hours to complete
6 videos (Total 114 min)
3 hours to complete
Neural Network and Deep learning
3 hours to complete
9 videos (Total 151 min)
Reviews
- 5 stars77.08%
- 4 stars14.58%
- 3 stars6.25%
- 1 star2.08%
TOP REVIEWS FROM 人工智慧:機器學習與理論基礎 (ARTIFICIAL INTELLIGENCE - LEARNING & THEORY)
by KJJan 3, 2022
Professor Ding's teaching is conscientious and the lectures are clearly explained
by ECAug 6, 2019
整體上, 是值得推薦的入門課程, 把machine learning的基本課程與熱門的topics提出來講. 習題的內容算簡單, 大部份在檢驗觀念.
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