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 first course of the two would focus more on mathematical tools, and the other course would focus more on algorithmic 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。本課程將較為著重數學類的工具，而另一課程將較為著重方法類的工具。]
機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations
National Taiwan UniversityAbout this Course
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Learner Career Outcomes
29%
started a new career after completing these courses
43%
got a tangible career benefit from this course
36%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 10 hours to complete
Chinese (Traditional)
Subtitles: Chinese (Traditional)
Skills you will gain
Decision StumpPerceptronMachine LearningVc Dimension
Learner Career Outcomes
29%
started a new career after completing these courses
43%
got a tangible career benefit from this course
36%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 10 hours to complete
Chinese (Traditional)
Subtitles: Chinese (Traditional)
Offered by
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/
Syllabus - What you will learn from this course
2 hours to complete
第一講：The Learning Problem
what machine learning is and its connection to applications and other fields
2 hours to complete
5 videos (Total 70 min), 5 readings
5 videos
What is Machine Learning18m
Applications of Machine Learning18m
Components of Machine Learning11m
Machine Learning and Other Fields10m
5 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
homework 010m
1 hour to complete
第二講：Learning to Answer Yes/No
your first learning algorithm (and the world's first!) that "draws the line" between yes and no by adaptively searching for a good line based on data
1 hour to complete
4 videos (Total 61 min)
4 videos
Perceptron Learning Algorithm (PLA)19m
Guarantee of PLA12m
Non-Separable Data12m
1 hour to complete
第三講：Types of Learning
learning comes with many possibilities in different applications, with our focus being binary classification or regression from a batch of supervised data with concrete features
1 hour to complete
4 videos (Total 61 min)
4 videos
Learning with Different Data Label18m
Learning with Different Protocol11m
Learning with Different Input Space14m
2 hours to complete
第四講：Feasibility of Learning
learning can be "probably approximately correct" when given enough statistical data and finite number of hypotheses
2 hours to complete
4 videos (Total 60 min)
4 videos
Probability to the Rescue11m
Connection to Learning16m
Connection to Real Learning18m
1 practice exercise
作業一40m
Reviews
TOP REVIEWS FROM 機器學習基石上 (MACHINE LEARNING FOUNDATIONS)---MATHEMATICAL FOUNDATIONS
by LLJun 23, 2018
This course give a theoretical analysis of machine learning,though there is not much introduction of algorithm in detail,but this helped me open a new door of machine learning.
by TTMar 3, 2018
I am very grateful to the teacher for bring me to the world of Machine Learing. I am new in the field. I will try my best to learn the basic knowledge of ML.
by XLApr 25, 2020
Really theoretical and challenging for somebody with little math like me. But very interesting to learn! Looking forward to the 2nd part.
by MCFeb 18, 2018
The speaker explains the ML in very clear and easier to understand way. I believe everyone can understand if he/she follow the course.
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