学生对 国立台湾大学 提供的 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations 的评价和反馈

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。

The speaker explains the ML in very clear and easier to understand way. I believe everyone can understand if he/she follow the course.

Lin is a very funny teacher.The course is really valuable.i will recap this course many times.thanks teacher lin again.thks

机器学习的数学和统计学基础本是让人望而生畏的部分，但林老师的讲解深入浅出，循序渐进，在有限的时间内让我领略了机器学习背后的原理，为后续学习机器学习算法增加了信心，非常感谢林老师的课程！

以前曾在台大上过课，对台大老师授课循序渐进的思路十分钦佩。这绝对是一门能够吸引学生全神贯注听讲的机器学习课程。没有复杂的推导，有生动的例程和老师细心的讲解，可以推测老师一定是花了许多心血经营这门课程。

基石上是很基础的一些知识，VC等等，不过我觉得作为想搞应用的人来说，这些底层数学原理不用学的那么详细，理解含义和思想即可，但是知道这些还是必须的！

这个课程对于原理的解释比较细致，能知其然也知其所以然，很棒！

林老师知道怎样把一个什么都不懂的学生教会，让他听懂。从这一点看，老师真的非常用心地在准备。在此对林老师的付出表示由衷的感谢！那句话这么说来着 douxia！

講得很清晰，而且從「演算法為什麼可以學習」切入，是其他課程比較少聽到的講解角度，很推薦

理论性很强，理性认识和感性认识结合

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.

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.

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.

Though I know many machine algorithms, but I've never thought about WHY machine can learn. This course let me know (to some extent) the fundamental issue.

Thank Prof. Lin and coursera for providing me with the platform and courses to make me better. Last but not least, the quiz is quite difficult...

wonderful class !

the teacher from NTU is quite humorous and gives class in an interesting and simple way! highly recommended!

Hard for mathmatical reasons, which made a solid fundation. Should recall or relearn math if you really wanna do sth on ML.

Theoretically explained why machine learning is feasible. The content is a little bit hard to understand.

以比較數學理論的角度解析機器學習，並且作為立論導入機器學習的領域，數學的部分真的蠻有難度，需要去思考一下，但是整體來說對於機器學習的概念有非常大的幫助，甚至可以藉由這些理論在一些案例中進行修正，非常有幫助。

A great theoretical course in machine learning, and looking for he second part of the math foundation

Very well structured course. It really helps building my basic understanding about machine learning

Good course, which help me understand mathematical foundations about machine learning!

Very Very wonderful course of theory about machine Learning, Very useful, thank you.

If the answer and the explanation of the homework are provided, it will be better.

This is a very nice courses. But I think the test is super hard for some students.