Вернуться к Mathematics for Machine Learning: Linear Algebra

# Отзывы учащихся о курсе Mathematics for Machine Learning: Linear Algebra от партнера Имперский колледж Лондона

4.7
звезд
Оценки: 9,571
Рецензии: 1,930

## О курсе

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....

## Лучшие рецензии

EC
9 сент. 2019 г.

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.

PL
25 авг. 2018 г.

Great way to learn about applied Linear Algebra. Should be fairly easy if you have any background with linear algebra, but looks at concepts through the scope of geometric application, which is fresh.

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## 101–125 из 1,923 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Xin Y

9 апр. 2020 г.

This is an excellent course as a refresher of the basic concepts in my college linear algebra. The instructors really put a lot of effort into making all the course materials. I enjoy the animations a lot! I am not a pro in Pandas but the programming assignments are actually very well-explained and perhaps a bit too easy. I'd thought they would put some plots and twists in the programming assignments. Very helpful course and great instructors. Thank you!

автор: Maximiliano B

24 мая 2020 г.

This course is excellent and it provided me a very good refresh about the linear algebra theory that I’ve learned in my graduate studies. The professor are great, the videos have an appropriate duration, and they help you build the intuition incrementally every week. The Python assignments are relative easy but they are of great value. I definitely recommend this course and I am looking forward to start the next course of the specialization.

автор: Orlando F P

24 мая 2020 г.

A comprehensive course in Mathematics and Linear Algebra. If you're not related, or with rusted maths, don't be afraid, it will work for you, but it will demand some amount of time. A good time of course. Here I learned things I didn't fully understand. Great teachers. Some misses on explanations, will push you to Khan, tutorials, or books. Recommended course for everyone interested in getting in ML, AI, DS. A great introductory course.

автор: Natasha M D

27 авг. 2020 г.

Excellent course for those who like me struggle with intuition of math behind machine learning. This is not for beginners and it is not a general linear algebra course, it assumes that you have already a good grasp of the theory. The course for me took the theory I had and increased my level of understanding in how to apply it to machine learning. Also the videos are fantastic, I've never been so enthusiastic about doing math before :D

22 окт. 2020 г.

As a student of mathematics, I have read linear algebra in 2nd year in my university. But I keep finding the application of linear algebra. This course introduce a new way exploring linear algebra core topics. All the course video,practice quiz and assignment and graded quiz are excellent. Specially I like the Eigen theory problem and visualising matrices and vectors part. Thanks all the course instructor and Imperial college London.

автор: Prateek A

22 июня 2020 г.

Very very excellent course on Linear Algebra by Imperial College of London :

I would like to thank @David Dye for teaching the intuition and essence of Linear Algebra.

Also @Sam Cooper, what a great teacher he is, couldn't wait to start the next course of the Specialization.

The best thing about this course is that whatever we learned, we applied all the stuffs side by side in ML.

Absolutely enjoyed the course. Thank You Coursera

автор: Harsh D

3 мая 2020 г.

Certainly the best online courseware I have attended. Prof. Dye breaks down most typical concepts of mathematics in simple and easy to understand blocks that makes this course fit for anyone. He brings out an interesting dimension to every concept that makes you comprehend it well and you're equipped to understand the practical applications of it. Would recommend to anyone looking brush their concepts of linear algebra.

автор: ChristopherKing

22 мар. 2018 г.

This is such a great course for student already have background about college level linear algebra knowledge, but don't know the under relationship among those terminologies. For instance, after this course I finally know what is dot product means, what is eigen characteristics. The content of this course are well prepared, this is such a masterpiece from Imperial College London. Thanks to all stuff behind this course.

автор: Srutimala D

12 мая 2020 г.

The connection between machine learning ad vectors got clearer as the course moved ahead. The quizes are detailed and requires actual understanding of the concept which is not hard to grasp once you pay attention to the lecturers who themselves are so passionate about the subject, makes me excited to learn too. I can say, I finally, after leaving high school, have understood high school maths and it's applications.

автор: Ashish D S

9 апр. 2018 г.

This is excellent course on Linear Algebra. The best part of this course is, lectures focus on the physical interpretation of the topics rather than making you practice formulae without understanding. This course helped me refresh my Linear Algebra concepts and also helped me better understand change of basis and Eigen related concepts.

Many many thanks to professors for excellent course design and presentation.

автор: Ritesh S

28 июня 2020 г.

No one can hate mathematics. The only reason you hate it or don't visualize it is because you never had an instructor who could do it. But, this course solves this problem with beautiful designed course content and intuitive quizzes that help you understand the underlying concepts on a broader perspective. Want to understand and visualize the basics of Linear Algebra used in ML, this is the course to apply to.

автор: Raja K

29 мая 2020 г.

awesome content with excellent pace. no bullshit during lectures. only place for improvement would be to give relevant content in readings as the course feels just of videos and less reading materials for reference. Ofcourse ,one can look up in textbooks , but giving the reading materials in the course will improve the readability and findability and will be according to the lecture content. thanks for asking!

автор: Vincent L

9 июня 2018 г.

I took this course as a review for my data science curriculum. Previously, I was having trouble recalling the details of matrix arithmetic which was making it hard for me to get a deeper understanding of machine learning. After doing this course, you should have no trouble following along. For those already familiar with the material, it should take about 1-2 weeks to complete if working at a leisurely pace.

автор: Thuy T N

7 авг. 2020 г.

This is my first encounter with Linear Algebra and surely the course has been extremely helpful beginner-friendly. I recommend investing in practical mathematics courses as this specialization if you are new to machine learning field. You will be equipped with enough math background and should feel confident to enter more technical machine learning/deep learning courses.

A truly fundamental stepping stone!

автор: Joseph F

20 июня 2019 г.

This course is perfect for many including those, like myself, who haven't seen this for 20+ years. I can imagine that it would be helpful to have, at least, a proclivity towards programming if you do not have familiarity with a programming language (at least course comments tend to reflect this).

For those experienced with coding, no difficulty will be encountered, as focus here is trivial (numpy libs).

автор: Digeesh J

21 мая 2020 г.

This course is good for everyone, as rather than diving deep in the paper pen model, the intuition is taught. For those who already know Linear Algebra, it is best to take this course to understand, what you are writing and what each formulae is doing. For those who dont know anything about Linear Algebra, but is interested in Machine Learning, do this course to atleast have the intuition behind it.

автор: Sertan A

12 июля 2020 г.

It's a very fundamental necessity for getting a hold on vectors and functions within a big programs. I have finished Mr. David Dye's part and he is an extraordinary teacher! I know Mr. Samuel Cooper from the calculus course and I assume his course will be quite awesome as well!! Thank you for making this available for people who need to upgrade their understanding, I respect this global mission!!!

автор: Mohiddin S

1 мая 2020 г.

I am very grateful to the in structures and the platform providers who designed the the course to enrich the knowledge of mathematics in good manor. From this course I learned a lot. Being a mathematician I feel that there is a need to change form traditional teaching to technological oriented teaching. This course helped me in finding such a path.

Thanking you

regards

Dr.Shaik Mohiddin Shaw

автор: Edisson A

29 апр. 2020 г.

Great course as a starter to understand the basis of linear algebra in machine learning. I had already taken a course of linear algebra as an undergrad but this course really opened my view of the applications and importance of some concepts I understood in a merely abstract way. The instructors are not only excellent in their explanations but you can also feel their interest for the subject.

автор: Lisa M

7 апр. 2018 г.

This was a fantastic course. I'm new to linear algebra, so it was bit intimidating even signing up (!) - but the lecturers were really, really good about explaining all concepts from the ground up so it was always possible to visualize and extrapolate from solid foundations. For me it was a stretch each week, but in a good way: very challenging, but achievable with enough planning and effort.

автор: Wasif S

3 авг. 2020 г.

This course for me was meant to be a habit-refiner but ended up being thinking of more into the depths of the world around. Very good course. The quiz & assignments are really good. Although some of the details are missing from particular sections, I think it will grow over time. As a Machine Learner's intro to perspective, this is really been a decent exercise to flex yourself. Goodluck.

автор: Ying T

9 мар. 2018 г.

An awesome course with high quality video lectures!! I will recommend this course to anyone who's looking for a refresher or quick pick-up on linear algebra. The homework's compatible with the materials and is quite interesting. The lecturer also did a good job on explaining critical concepts with easy but good examples. I'm looking forward to more similar courses from Imperial College.

автор: Jayant V

29 мар. 2018 г.

I have taken a course on linear algebra during my graduate program and must admit that it was not one of my more comfortable ones! Coming back to this course online, it really did help me get a much better understanding of concepts like dimensionality, basis, eigen values and eigen vectors. I intend to go over the lectures at least a few more times to be sure I have understood it well.

автор: SHOUNAK B

12 июля 2020 г.

I personally loved this course as it changed my outlook and perspective towards Mathematics in computing and as a whole. I really enjoyed taking this course. It got me into some difficult assignments but the joy of solving it after lots of brainstorming and discussing with peers was awesome experience. I look forward towards developing myself and gaining knowledge with these courses.