Mathematics for Machine Learning: Linear Algebra(으)로 돌아가기

4.7
별점
10,863개의 평가

## 강좌 소개

In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

## 최상위 리뷰

CS

2018년 3월 31일

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

NS

2018년 12월 22일

Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.

필터링 기준:

## Mathematics for Machine Learning: Linear Algebra의 2,180개 리뷰 중 2051~2075

교육 기관: Santiago R R

2020년 6월 20일

The assignments kill this course, great instructors, and pace, in my opinion. (I am a beginner in linear algebra and I understood the concepts without needing Google or external resources)

교육 기관: Rong D

2018년 8월 30일

I think the course is more suitable for those who have had comprehensive theoretical knowledge in linear algebra and intend to learn more about its practical use and its relevance to code.

교육 기관: Marcus V C A

2021년 5월 23일

The course is good. But the last module (week) is not so good. I think that the explanation of the Page Rank algorithm is not very good. I also think that the final test is very confuse.

교육 기관: TirupathiRao p

2020년 5월 16일

Overall course was good, I have learnt few new concepts which I haven't know till now. But at the end, things were not clear while putting all together for solving page rank algorithm.

교육 기관: David D

2020년 8월 18일

Linear Algebra content is great, however, was not aware that a huge portion of grade is based on Python programming exercises!!! Only need to learn Linear Algebra, not programming!!!

교육 기관: Aurel N

2020년 5월 8일

Intuitive geometrical representations of eigenvalues and eigenvectors in 3blue1brown style. Had some concerns with a few theoretical inaccuracies of the material presented.

교육 기관: Akeel A

2020년 7월 22일

It was a good to review linear algebra again and see how what I learned in my first year course at university could be applied here! Plus it was good to see Python again.

교육 기관: Manuel M

2019년 1월 25일

The course feels very disorganized in general. Some quizzes are about 10 standard deviations from the average difficulty, which is befuddling to say the least.

교육 기관: itwipsy17

2020년 2월 25일

It is good course for machine learning. But I didn't fully understand the page rank system with damping.

More explanation of damping is needed for the newbie.

교육 기관: vignesh n

2018년 9월 12일

Transition from explanation of basic to advanced concepts could have been better. There was an assumption that few things was already know to the learner.

교육 기관: Alexander D

2018년 8월 7일

Not enough focus on how material connects to machine learning. A case study example would help, as would a very slow, detailed step-by-step illustration.

교육 기관: Santiago M

2020년 9월 14일

Nice one. But realized I needed more foundation on this matter. So decided to abandon and level up my topic knowledge in Khan Acadamy. I will be back.

교육 기관: Sanyam G

2022년 4월 3일

Good for someone who has bit background in Linear Algebra and Python. I won't recommend this work for a completely newbie as this course lacks depth.

교육 기관: Cindy X

2018년 12월 20일

I think this course is a little bit hard for a beginner with python. And I hope that the teacher can talk more about the Machine learning part.

교육 기관: Christos G

2021년 1월 24일

Very good explanations on difficult subjects but a bit short coverage of various cases, thus some assignments and quizzes were challenging.

교육 기관: Atish B

2020년 9월 24일

Answers to Several questions in Week 5 quiz around eigen values and eigen vectors need to be revisited as they donot appear to be correct.

교육 기관: Serdar D

2021년 2월 15일

This course consists of very fundamentals of linear algebra. I expected advanced linear algebra contents and more software applications.

교육 기관: Amal J

2020년 7월 15일

The course gives a good beginner-friendly Introduction to Linear Algebra. But the courses could cover a little more topics in LA.

교육 기관: Jorge G

2020년 8월 14일

I would give it 3.7, examples are good but the vectors the lecturer draw were no easy to understand because of drawing by hand.

교육 기관: Nicholas G

2022년 6월 21일

TEverything is good until you reach the coding assignement. Then it is a complete disconnect with no resources available.

교육 기관: Badri T

2019년 12월 29일

The Eigen system could have been better explained. The last quiz was too hard and the concepts required were not covered

교육 기관: Aaron H

2019년 10월 17일

Lot of the concepts seemed glossed over and could have used more guided practice and/or linkages to real world problems.

교육 기관: Indira P

2021년 3월 7일

It is so complex and contains so much knowledge but hard to understand for beginner or intermediate in mathematic

교육 기관: Kate G

2020년 11월 19일

The instructor is skipping a lot of material and the quizzes require working with external sources to be solved.

교육 기관: Matt P

2019년 2월 24일

This course would be perfect if more elaboration on the maths required to complete the quizzes, was provided.