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。]
이 강좌에 대하여
학습자 경력 결과
12%
33%
43%
학습자 경력 결과
12%
33%
43%
제공자:

국립 타이완 대학
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.
강의 계획 - 이 강좌에서 배울 내용
第九講: Linear Regression
weight vector for linear hypotheses and squared error instantly calculated by analytic solution
第十講: Logistic Regression
gradient descent on cross-entropy error
第十一講: Linear Models for Classification
binary classification via (logistic) regression; multiclass classification via OVA/OVO decomposition
第十二講: Nonlinear Transformation
nonlinear model via nonlinear feature transform+linear model with price of model complexity
검토
機器學習基石下 (MACHINE LEARNING FOUNDATIONS)---ALGORITHMIC FOUNDATIONS의 최상위 리뷰
What an amazing course! I hope professor can give new courses in the future and cover more practical things with so hard theoretical things.
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。
I learned machine learning theory from this course. This is very useful.
Great course on soliciting basics of ML! Looking forward to next one.
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