The course extends the fundamental tools in "Machine Learning Foundations" to powerful and practical models by three directions, which includes embedding numerous features, combining predictive features, and distilling hidden features. [這門課將先前「機器學習基石」課程中所學的基礎工具往三個方向延伸為強大而實用的工具。這三個方向包括嵌入大量的特徵、融合預測性的特徵、與萃取潛藏的特徵。]
Offered By
機器學習技法 (Machine Learning Techniques)
National Taiwan UniversityAbout this Course
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Flexible deadlines
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Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 18 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. 18 hours to complete
Chinese (Traditional)
Offered by
Syllabus - What you will learn from this course
2 hours to complete
第一講:Linear Support Vector Machine
2 hours to complete
5 videos (Total 67 min), 4 readings
1 hour to complete
第二講:Dual Support Vector Machine
1 hour to complete
4 videos (Total 60 min)
1 hour to complete
第三講:Kernel Support Vector Machine
1 hour to complete
4 videos (Total 61 min)
1 hour to complete
第四講:Soft-Margin Support Vector Machine
1 hour to complete
4 videos (Total 46 min)
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