What Is Programming? And How To Get Started
January 28, 2025
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Instructor: 林軒田
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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。]
weight vector for linear hypotheses and squared error instantly calculated by analytic solution
4 videos4 readings
gradient descent on cross-entropy error to get good logistic hypothesis
4 videos
binary classification via (logistic) regression; multiclass classification via OVA/OVO decomposition
4 videos
nonlinear model via nonlinear feature transform+linear model with price of model complexity
4 videos1 assignment
overfitting happens with excessive power, stochastic/deterministic noise and limited data
4 videos
minimize augmented error, where the added regularizer effectively limits model complexity
4 videos
(crossly) reserve validation data to simulate testing procedure for model selection
4 videos
be aware of model complexity, data goodness and your professionalism
4 videos1 assignment
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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.
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Reviewed on Oct 2, 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。
Reviewed on Oct 7, 2021
Really great theoretical machine learning course!
Reviewed on Aug 12, 2020
I learned machine learning theory from this course. This is very useful.
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