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Retour à 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations, Université nationale de Taïwan

603 notes
111 avis

À propos de ce cours

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。]...

Meilleurs avis

par LL

Jun 24, 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.

par TT

Mar 04, 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.

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109 avis

par 陈宇轩

May 18, 2019

Very impressive

par 陈千奔

May 11, 2019


par TED

Apr 26, 2019

incredible amazing course,thank you, prof.lin

par Allen Lin

Apr 01, 2019

very good

par 王达光

Mar 19, 2019


par playHing

Feb 23, 2019

the best course ever!

par Hong Hu

Feb 09, 2019

Other course only tells me how to use ML but this course tells me to how to deep-in understand ML foundations. I am very grateful to the teacher, 林軒田. Thank you soooo much.


Jan 13, 2019

Instructions were clear and good. I might just need to review it more times, but the first time I did feel that sometimes we've gone way into the weeds with the math and I lost the big picture - why are we looking at this equation to begin with? Maybe what would be beneficial is to have a concrete example that threads through the entire class and refer back to it to illustrate why we care about certain properties.

par dalaozi

Dec 24, 2018


par Yixin Bao

Dec 14, 2018