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Voltar para 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

Comentários e feedback de alunos de 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations da instituição Universidade Nacional de Taiwan

4.9
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785 classificações
143 avaliações

Sobre o curso

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。]...

Melhores avaliações

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.

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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126 — 140 de 140 Avaliações para o 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

por ZIAN X

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.

por ziqin l

Aug 27, 2020

林老师这部分课程内容偏理论,对数理基础有一定的要求。每次作业题需要认真思考,作业后面的编程部分也能锻炼实践能力,进一步巩固所学习的理论知识。总体来说质量不错,不过希望老师以后能以后对课件里面的问题进行总结的时候可以不用太story-like,或者说更简练一点,我认为这样可以有助于学习暂停视频并好好理解。

por Xuechen L

Apr 26, 2020

Really theoretical and challenging for somebody with little math like me. But very interesting to learn! Looking forward to the 2nd part.

por Jiazhi G

Aug 18, 2017

許多名詞似乎是自創新詞,但都能很好地描述ML的理論

課程的統計很吃重,難度的分配有些不均勻

整體來說是非常適合有數學底子學生的扎實入門課程

por 王博洋

Aug 07, 2017

林老师讲课很好,但是希望老师在讲到一些比较容易混淆的概念的时候,可以举一些例子帮助我们加深理解。

por Gao C

Jan 03, 2018

课程不错,不过很多章节需要多看两遍才能清楚理解

por yu c p

Jun 08, 2019

理論較深,也和其他機器學習課程起點不太一樣

por alexhanbing

Aug 29, 2018

VC等在当前的指导意义不是很大,整体不错

por 黄鑫荣

Oct 11, 2018

问题的切入点怪怪的,不如吴恩达的易懂

por ZhengLiangLiang

Dec 24, 2017

课上得特别好 但是习题给的提示不够

por Qier W

Aug 13, 2020

great cours!

por 李瑞平

Apr 26, 2018

偏重于机器学习的理论基础

por Jyh1003040

May 11, 2020

This course is not as fantastic as it is widely advertised. The material taught is not enough to cope with the difficulty of homework. If you have ample time and support this course would be great, otherwise, it is not very self-contained.

por Daya_Jin

Jun 11, 2018

完全不推荐!这门课讲的全是 机器学习中的前提与假设,并且很多概念被老师复杂化了,可能老师拐弯抹角的讲某些概念的本意是为了学生更好的理解,但是真的讲得更复杂了。除非对机器学习的发展历史有执念、或者是专门深入研究机器学习的人,否则不推荐这门课,更推荐吴恩达和李宏毅的课。PS:本人专业硕士,方向机器学习,这门课中的很多东西我都用不上! 可能有志于学术方面的学硕或博士用得上。

por Ananya A

Sep 23, 2020

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