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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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.
Intermediate Level
Approx. 11 hours to complete
Chinese (Traditional)
Offered by
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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