About this Course
4.9
142 ratings
26 reviews
Machine learning is the study that allows computers to adaptively improve their performance with experience accumulated from the data observed. Our two sister courses teach the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. This second course of the two would focus more on algorithmic tools, and the other course would focus more on mathematical tools. [機器學習旨在讓電腦能由資料中累積的經驗來自我進步。我們的兩項姊妹課程將介紹各領域中的機器學習使用者都應該知道的基礎演算法、理論及實務工具。本課程將較為著重方法類的工具,而另一課程將較為著重數學類的工具。]...
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100% online courses

Start instantly and learn at your own schedule.
Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Clock

Approx. 12 hours to complete

Suggested: 6 hours/week...
Comment Dots

Chinese (Traditional)

Subtitles: Chinese (Traditional)...
Globe

100% online courses

Start instantly and learn at your own schedule.
Calendar

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Clock

Approx. 12 hours to complete

Suggested: 6 hours/week...
Comment Dots

Chinese (Traditional)

Subtitles: Chinese (Traditional)...

Syllabus - What you will learn from this course

Week
1
Clock
2 hours to complete

第九講: Linear Regression

weight vector for linear hypotheses and squared error instantly calculated by analytic solution...
Reading
4 videos (Total 62 min), 4 readings
Video4 videos
Linear Regression Algorithm20m
Generalization Issue20m
Linear Regression for Binary Classification11m
Reading4 readings
NTU MOOC 課程問題詢問與回報機制1m
課程大綱10m
課程形式及評分標準10m
延伸閱讀10m
Week
2
Clock
1 hour to complete

第十講: Logistic Regression

gradient descent on cross-entropy error to get good logistic hypothesis...
Reading
4 videos (Total 65 min)
Video4 videos
Logistic Regression Error15m
Gradient of Logistic Regression Error15m
Gradient Descent19m
Week
3
Clock
1 hour to complete

第十一講: Linear Models for Classification

binary classification via (logistic) regression; multiclass classification via OVA/OVO decomposition...
Reading
4 videos (Total 59 min)
Video4 videos
Stochastic Gradient Descent11m
Multiclass via Logistic Regression14m
Multiclass via Binary Classification11m
Week
4
Clock
2 hours to complete

第十二講: Nonlinear Transformation

nonlinear model via nonlinear feature transform+linear model with price of model complexity...
Reading
4 videos (Total 59 min), 1 quiz
Video4 videos
Nonlinear Transform9m
Price of Nonlinear Transform15m
Structured Hypothesis Sets9m
Quiz1 practice exercise
作業三40m

Instructor

林軒田

教授 (Professor)
資訊工程學系 (Computer Science and Information Engineering)

About National Taiwan University

We firmly believe that open access to learning is a powerful socioeconomic equalizer. NTU is especially delighted to join other world-class universities on Coursera and to offer quality university courses to the Chinese-speaking population. We hope to transform the rich rewards of learning from a limited commodity to an experience available to all. More courses information, the official Facebook Page: https://www.facebook.com/ntumooc2017/...

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.