About this Course
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Flexible deadlines

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Intermediate Level

Approx. 12 hours to complete

Chinese (Traditional)

Subtitles: Chinese (Traditional)
Learners taking this Course are
  • Machine Learning Engineers
  • Data Scientists
  • Data Analysts
  • Technical Solutions Engineers
  • Data Engineers

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 12 hours to complete

Chinese (Traditional)

Subtitles: Chinese (Traditional)

Syllabus - What you will learn from this course

Week
1
2 hours to complete

第九講: Linear Regression

4 videos (Total 62 min), 4 readings
4 videos
Linear Regression Algorithm20m
Generalization Issue20m
Linear Regression for Binary Classification11m
4 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
1 hour to complete

第十講: Logistic Regression

4 videos (Total 65 min)
4 videos
Logistic Regression Error15m
Gradient of Logistic Regression Error15m
Gradient Descent19m
Week
3
1 hour to complete

第十一講: Linear Models for Classification

4 videos (Total 59 min)
4 videos
Stochastic Gradient Descent11m
Multiclass via Logistic Regression14m
Multiclass via Binary Classification11m
Week
4
2 hours to complete

第十二講: Nonlinear Transformation

4 videos (Total 59 min), 1 quiz
4 videos
Nonlinear Transform9m
Price of Nonlinear Transform15m
Structured Hypothesis Sets9m
1 practice exercise
作業三40m
4.9
41 ReviewsChevron Right

17%

got a tangible career benefit from this course

25%

got a pay increase or promotion

Top reviews from 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

By HLDec 5th 2017

What an amazing course! I hope professor can give new courses in the future and cover more practical things with so hard theoretical things.

By JJOct 3rd 2018

很好的课程,更加注重算法的理论推导,当然也不乏运用的技巧。之前看过吴恩达老师的机器学习课程,感觉林老师这门课更加的深入,吴恩达老师的课省去了公式的推导,更偏向工程的实践,两门课可以算是相辅相成的。

Instructor

Avatar

林軒田

教授 (Professor)
資訊工程學系 (Department of 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.

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