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

임페리얼 칼리지 런던의 Mathematics for Machine Learning: Linear Algebra 학습자 리뷰 및 피드백

10,709개의 평가
2,130개의 리뷰

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


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.


2021년 8월 8일

the instrutors were too good and their explination for the concepts was to the point and it made me realize things in linear algebra I didn't know before although I studied it in school of engineering

필터링 기준:

Mathematics for Machine Learning: Linear Algebra의 2,142개 리뷰 중 1676~1700

교육 기관: RITIK D E

2020년 5월 1일

Course was very interesting but found some difficulties in the assignment section as it took almost hour to understand it. But, the course was very nice and also it help me to recollect all the mathematics part of Linear Algebra that I've studied earlier.

교육 기관: Aarón M C M

2019년 6월 5일

I am a computer scientist and this course served me to refresh all that concepts and exercises that I studied at the university, I only would ask to improve of the notebook's availabilty because sometimes I got disconnected and had to start all over again.

교육 기관: Akiva K S

2020년 5월 30일

Multiplying 2x2 matrices by hand drives me crazy! Why instructors waste precious online time on that crap? Two, three matrix multiplications by hand during the lecture is perfectly OK with me, but why to do it over and over? The same with the exercises.

교육 기관: Xiaocong Y

2021년 2월 15일

Good for beginner, but relatively easy if you have backgrounds in Linear Algebra. The course focus on making you adopt intuitions of how Linear Algebra is actually working geometrically which may be interesting if you only knows how the algebra works.

교육 기관: Joshua P

2020년 7월 9일

As someone with a bit of a background in linear algebra, this course is perfect in being a refresher to the said course. But unfortunately, especially for those who are completely new to the subject, the hurried explanations will leave some confused.

교육 기관: Jehan T

2020년 8월 9일

Great course, especially the first 4 weeks with David Dye. Unfortunately the lecturer in the 5th week is much harder to follow, and I needed to reference some additional youtube videos outside the course to get an intuitive grasp of the concepts.

교육 기관: David B C

2018년 9월 8일

Great lectures and wonderful scrutiny of matrices and vectors. Exploration of machine learning using Python, but the interface and project upload are somewhat kludgy. Stick with it and you can get the fundamentals even if the coding doesn't work.

교육 기관: Priadi T W

2019년 9월 7일

The course was great for me. It opens up new perspective to some vector and matrix application. However, I must admit that you must have strong background with math before taking this course, as I was little bit struggling with matrix part.

교육 기관: Marcin

2018년 6월 4일

It's by far the toughest course that I've done on Coursera. And at the same time the most rewarding upon completion. The course content is very applicable in the real world and it's definitely something that any ML specialist should know.

교육 기관: Srinivas A

2020년 7월 7일

Great content, well explained, it's an overview of Linear Algebra relevant to Machine Learning, not a full blown course. Some of the assignments need clarity, especially the Python assignments. There is no faculty/staff to ask questions.

교육 기관: Mikko V

2018년 8월 1일

The lectures are excellent, but the scarcity of traditional math assignments prevented intuitive and reinforced learning. Thus the course should be considered a brief glance at linear algebra, rather than a proper course on the subject.

교육 기관: Yadla V C

2020년 10월 19일

This Course takes you to the deep dive of Linear Algebra. But the lectures are not sufficient to solve assignments. We can make use of the resources given by Instructors for clear understanding of core concepts of Vectors and Matrices

교육 기관: Godugu A H

2021년 11월 30일

T​he course overall is very good. The only drawback I felt was the lack of numerical examples to intepret complex linear algebra formulae. I would love to see videos carrying more worked examples of the formulae learnt in the course.

교육 기관: Gady

2020년 3월 26일

The pedagogy could use some reviewing, but the concepts and especially the reviews are generally laid out logically, and relatively easy to go through. Still recommend looking up things on the side through YouTube when you're stuck.

교육 기관: Rohit S

2020년 3월 3일

There were many concepts which were totally new to me and many were known to me but I couldn't relate them with the machine learning problems now an I am able to do all those problems easily so thanks a lot Coursera and ICL team.

교육 기관: Akshay V

2020년 7월 14일

It is a good course on Linear Algebra. The teaching was excellent, all the assignments were challenging with some easy ones in the middle to boost your learning process, altogether I am happy to cover it with good understanding.

교육 기관: Mit S

2020년 2월 24일

This course has great content and great way of teaching by instructors however the instructions in the programming exercises is not very clear. I hope the instructors take note of that. Overall, a fantastic Course content wise!

교육 기관: Sekhar G

2020년 8월 20일

Being at an advance level of study, this course seems to easy to me but what I recommend is that any undergraduate or postgraduate student will definitely gain many interesting facts about linear algebra from this course.

교육 기관: Carlos M V R

2020년 7월 25일

It could be good to have more explanation about eigenvalues and eigenvectors because it is an important topic for data science. In general it is a very good course, you explained many topics in a simple and funny way.

교육 기관: Arnab S

2020년 6월 21일

I enjoyed learning in this course. There are a lot of different aspects that are covered here which is very interesting but I course is not for absolute beginners. It will be better if someone has a bit of background.

교육 기관: Bassiehetkoekje

2019년 2월 27일

Nicely structured courses with enthusiastic teachers. Interactive enough to keep you thinking (which is key).

Some errors here and there and short moments of not enough explanation. But all in all an enjoyable course.

교육 기관: Naser A A

2020년 7월 11일

Great course to understand how linear algebra is related to machine learning. Focused on the concepts, and the concepts work rather than calculations. Would be easier if there was prior knowlodge of python and numpy.

교육 기관: Cici

2019년 7월 12일

This is a great course. The only thing is sometimes the calculations are hard to follow. I wonder if it is possible to let viewers click through a calculation process at their own pace. But the instructors are great!

교육 기관: Mrunal U

2020년 7월 20일

excellent course to understand the linear algebra as a tool for problem solving in machine learrning though it not help directly but give you the strong understanding the fundamentals which will help in the future

교육 기관: Snigdha A

2020년 10월 13일

Excellent course. I just wish the assignments were a little harder. The last assignment was the perfect toughness level. Made me connect concepts, look up stuff and actually get out of my comfort zone to learn.