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。]
von
機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations
National Taiwan UniversityÜber diesen Kurs
31,933 kürzliche Aufrufe
Karriereergebnisse der Lernenden
29%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
43%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
36%
erhalten Sie eine Gehaltserhöhung oder Beförderung
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 10 Stunden zum Abschließen
Chinesisch (traditionell)
Untertitel: Chinesisch (traditionell)
Kompetenzen, die Sie erwerben
Decision StumpPerceptronMachine LearningVc Dimension
Karriereergebnisse der Lernenden
29%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
43%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
36%
erhalten Sie eine Gehaltserhöhung oder Beförderung
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 10 Stunden zum Abschließen
Chinesisch (traditionell)
Untertitel: Chinesisch (traditionell)
von
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/
Lehrplan - Was Sie in diesem Kurs lernen werden
2 Stunden zum Abschließen
第一講：The Learning Problem
what machine learning is and its connection to applications and other fields
2 Stunden zum Abschließen
5 Videos (Gesamt 70 min), 5 Lektüren
5 Videos
What is Machine Learning18m
Applications of Machine Learning18m
Components of Machine Learning11m
Machine Learning and Other Fields10m
5 Lektüren
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 Stunde zum Abschließen
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 Stunde zum Abschließen
4 Videos (Gesamt 61 min)
4 Videos
Perceptron Learning Algorithm (PLA)19m
Guarantee of PLA12m
Non-Separable Data12m
1 Stunde zum Abschließen
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 Stunde zum Abschließen
4 Videos (Gesamt 61 min)
4 Videos
Learning with Different Data Label18m
Learning with Different Protocol11m
Learning with Different Input Space14m
2 Stunden zum Abschließen
第四講：Feasibility of Learning
learning can be "probably approximately correct" when given enough statistical data and finite number of hypotheses
2 Stunden zum Abschließen
4 Videos (Gesamt 60 min)
4 Videos
Probability to the Rescue11m
Connection to Learning16m
Connection to Real Learning18m
1 praktische Übung
作業一40m
Bewertungen
Top-Bewertungen von 機器學習基石上 (MACHINE LEARNING FOUNDATIONS)---MATHEMATICAL FOUNDATIONS
von LL23. Juni 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.
von TT3. März 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.
von XL25. Apr. 2020
Really theoretical and challenging for somebody with little math like me. But very interesting to learn! Looking forward to the 2nd part.
von MC18. Feb. 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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