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

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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....

HE

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

EC

2019년 9월 9일

Excellent review of Linear Algebra even for those who have taken it at school. Handwriting of the first instructor wasn't always legible, but wasn't too bad. Second instructor's handwriting is better.

필터링 기준:

교육 기관: Matteo L

•2020년 4월 20일

I think this is a great review of linear algebra, especially for someone who has already previously studied the topics.

The example with the PageRank algorithm was very interesting and a great add to the course.

Possibly a downside of the course was a lack of practice of the material, especially considering how easy the notebook assignments are.

교육 기관: Carolyn O

•2021년 2월 26일

Goal is to get a gut feel through understanding math behind the python functions, but I wish they had start doing the code in parallel sooner. At end of the course, they accomplish this. Hand calculations in middle weeks were long enough to distract from the overview. It says its beginner course, but glad I had some background.

교육 기관: Yazhini P

•2020년 1월 26일

The course and the faculty were amazing altogether. All my queries regarding linear algebra were cleared and I began to look at linear algebra in a new eye.

The only flaw was inaccessibility to the correct Notebook link. Only after going through the forum was I able to get the correct link as it was, luckily, posted by someone.

교육 기관: Emmanuel G

•2021년 4월 14일

Covers some good basics, but I feel that I would have struggled with the programming assignments if I didn't already have some practical experience with data science in Python and linear algebra. In particular, the last 20% of the course felt (eigensystems) felt rushed and could have been expanded upon a bit more thoroughly.

교육 기관: Vinayak N

•2018년 10월 14일

Good for starters. It gives a holistic view of linear Algebra. Geometric interpretation of Eigen Vectors was the highlight of the course for me as I wasn't aware of it before and the instructor helped me understand the concept very well! Thanks for putting forth this course and hope to see more in the forthcoming sessions :)

교육 기관: Rick M

•2019년 7월 21일

Overall, I thought this course was worth the time. Some of the material was challenging, but the instructors were pretty good at explaining clearly. Just a head's up: there is relatively little reading material here, so if you struggle to learn through videos you might have a hard time. That part was a challenge for me.

교육 기관: Henri S

•2020년 10월 9일

Could be nice to have the complete mathematical definitions given in an annex for those that are interested in refreshing their maths more than understanding the concepts broadly throughout the examples. Otherwise very well taught, I like that there are many examples where you have to get back to basic calculations.

교육 기관: Simon W

•2020년 6월 27일

Good course overall and I enjoyed the top-down approach in instruction, which helped me understand the big picture before proceeding to do specific linear algebra computations. However, I wish there were more lecture contents and exercises to help me build a better foundation and clear up occasional confusions.

교육 기관: RICHARD A (

•2020년 6월 6일

The course already cover all some of essential topics in linear algebra is is a good course to refresh linear algebra and get hands on coding on how we can use linear algebra for computation. I would be great if the course also covers other essential topics such as null space, column space, pre-image, and image

교육 기관: Subham K S

•2020년 1월 30일

Great course!! The instructors taught in a great way with proper visualization and real-world applications.

But more examples of implementing in machine learning could have been included and a bit more concepts could have been taught.

Overall great one. Thank you coursera, Imperial college and both instructors.

교육 기관: Beyza A

•2020년 5월 3일

I have 2 years of experience with coding. I took this course to refresh my knowledge of mathematics before I start using machine learning techniques. This course sometimes gave us the basic knowledge which helped to apply real-world situations. However, I feel like I need more exercises, basic explanations.

교육 기관: Oriane N

•2022년 5월 3일

Very well explained with videos and a recap PDF. Guided exercices to practice with manual calculations and computer programming (Python notebooks) and questions to get the intuition of what's going on with special cases. I recommend and will continue the specialization with the other Maths for ML courses !

교육 기관: Sandeep M

•2022년 4월 30일

I really enjoyed the course. Great learning experience. There's one area where I felt that the course could have done better. And that is explaining the interpretations of various mathematical calculations. These interpretations were embedded in the quizzes and the assignments. But they were very cryptic.

교육 기관: Luis F H

•2020년 12월 10일

The videos and materials are great, departing from zero in the subject I was capable of understanding and practicing., but some programing exercises demand any knowledge in python, what makes things more difficult in a few moments. Would recommend for anyone that wants to enter into the ML world.

교육 기관: Chip B

•2019년 5월 25일

Filled in a lot of knowledge gaps that I should have learned in high school or undergrad. I feel much more prepared for graduate studies in data science.

4 stars because the last module felt rushed. I felt that I learned more from trial and error on the quiz than from the lecture videos.

교육 기관: Kun L

•2020년 7월 4일

The content is good, and I can see that the instructors are trying to let students understand the mechanism behind the calculations. However, the lectures are too short for students to fully understand everything. I would suggest to extend the length of the videos and provide more details.

교육 기관: Frank G

•2018년 4월 14일

Very good class. Outstanding instructors very clearly teaching key concepts in linear algebra.

I only docked one star for two reasons:

I wish they explained in more depth how the linear algebra topics are used in machine learning.

I wish the class were a little longer and more in-depth.

교육 기관: Sagar

•2020년 10월 23일

Mathematics is the core of machine learning. This course is best for understanding the mathematics of machine learning. The course was in-depth and intuitive. The assignments were a bit difficult for the new programmers. But overall, the theory classes were clear and understandable.

교육 기관: Sydney F

•2019년 7월 26일

While they explain the basic concepts of linear algebra, sometimes the programming assignments are tricky and some of the quizzes are too complicated to complete with our current knowledge. However, the course is worth taking if you want a solid math background for machine learning.

교육 기관: saurabh p

•2019년 3월 5일

the lectures were very good and on point, obviously referring the prescribed textbooks will further improve one's knowledge about the subject. i really enjoyed the programming part of the assignments, which were made to help students without any prior experience of python language.

교육 기관: Md. M H

•2018년 11월 1일

It would be better if it pointed out the pre-requisites of this course. Besides, the submission process of Jupyter notebook doesn't work directly. These issues need to be solved. Other than these issues, the course itself is pretty informative and the instructors are well prepared.

교육 기관: Nikhil G

•2018년 3월 30일

Great course, offers a nice introductory base you can use to further your knowledge without having to take a full three month course on linear algebra, allows you to dig into some interesting stuff earlier on. Could have used a bit more feedback for quizzes and assignments though.

교육 기관: Ziyi Z

•2020년 12월 26일

The lectures are easy to understand. However, the quiz is slightly harder than the course material. Especially the first quiz (it gets easier in the end). The coding part requires previous knowledge of python. Otherwise, you will be so lost in the process. Overall, great course.

교육 기관: SHUVA M

•2020년 7월 22일

The instructors were great. They explained the topics nicely. But this course should add more clarification of different topics in the video section. And it would be great if the instructors could add some programming examples in the videos. Then the course will be more helpful.

교육 기관: Kevin E

•2020년 4월 27일

The examples were relevant, and I could follow along with them on my own. The programming assignments helped to complete the understanding of the processes. I would've liked more examples to work through for practice, and to improve understanding. Otherwise, it was great.

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