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Вернуться к 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

Отзывы учащихся о курсе 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations от партнера Национальный университет Тайваня

4.9
звезд
Оценки: 292
Рецензии: 54

О курсе

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。]...

Лучшие рецензии

HL
4 дек. 2017 г.

What an amazing course! I hope professor can give new courses in the future and cover more practical things with so hard theoretical things.

JJ
2 окт. 2018 г.

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。

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1–25 из 54 отзывов о курсе 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

автор: Yijie Q

26 нояб. 2018 г.

最早知道林老师的机器学习基石和技法课程,还是Coursera改版之前的事。当时还在上学,挑选着章节,把林老师的讲解作为课堂内容的补充理解来听,当时就觉得林老师讲的特别棒,课堂上迷迷糊糊的内容来这里听一遍就好很多。现在工作了,终于能抽出时间来把整个课程完整的跟下来,仍然觉得受益匪浅。真的非常感谢林老师能够制作出这样用心的的课程,放在网上与大家分享,也感谢您和TA们从过去到现在一直关注着讨论区的动态,为大家答疑。谢谢!

автор: Jeff

3 окт. 2018 г.

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。

автор: lcy9086

18 апр. 2018 г.

林老師的課不僅聽起來比較清晰易懂,並且深度足夠(比Andrew Ng的課而言深度要大不少),值得多次聽講。作業質量也比較高,能夠有很好的鍛煉效果。期待後續的技法課程能夠在coursera上面公佈。

автор: Jeremy L

3 дек. 2017 г.

透過這次的測驗可以有助於了解自己的觀念是否還夠清楚,以及有沒有什麼地方需要再加強的。

автор: Ho K

5 июня 2019 г.

课程内容做到了理论与实践兼顾,作业内容非常棒,对进一步深化理解课程很有帮助

автор: honest a

17 февр. 2021 г.

CHinese!

автор: ZIAN X

4 февр. 2019 г.

Very good course for exactly what it's for - theoretical foundation. I wish there were more courses that aim at applying these techniques in practice with actual problems.

автор: Harry L

5 дек. 2017 г.

What an amazing course! I hope professor can give new courses in the future and cover more practical things with so hard theoretical things.

автор: 刘志伟

13 апр. 2019 г.

The best course for machine learning I ever met! Very recommended to those who want to build a solid foundation in machine learning.

автор: 徐森

17 нояб. 2019 г.

the ML isn't alchemy, from the parameters and regularization, we can interpret the model

автор: guanghaoli

13 авг. 2020 г.

I learned machine learning theory from this course. This is very useful.

автор: Ryan

15 апр. 2018 г.

A perfect course in spite of a little in-digestibility .

автор: t_xinxishijie

14 мар. 2018 г.

Very interesting course for me! I love it very much.

автор: Wang B

6 июня 2018 г.

good explaination the foundation of all ML models

автор: 刘沛奇

28 февр. 2021 г.

课程非常的有趣,讲的非常的细致,非常感谢!不知道有没有可能也加入一些LASSO优化求解的内容。

автор: Garfield

19 июня 2019 г.

amazing! Great course! thanks a lot!

автор: Tse-Yu L

18 февр. 2018 г.

Nice course, excellent course design.

автор: cheyao

13 янв. 2018 г.

excellent and clear teaching of ML

автор: Yen, Y

27 авг. 2018 г.

Best ML course I have ever taken!

автор: 何旭东

13 янв. 2021 г.

内容很有趣,但是如果能有更多关于code实战的材料或内容会更好

автор: QIQING

10 дек. 2018 г.

课程设计的极好!

确实是基石课,从原理到实践,恰到好处!

感谢!

автор: Chen X

29 янв. 2018 г.

good, but quiz is not enough.

автор: Andrew H

9 дек. 2018 г.

深入淺出,一個讚字,唯一美中不足是中文字幕偶爾有錯誤。

автор: huixiaoba

24 февр. 2018 г.

林老师讲的很好,让我对机器学习有了更加深入的了解。谢谢