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

별점

10,695개의 평가

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2,126개의 리뷰

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....

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.

PL

2018년 8월 25일

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.

필터링 기준:

교육 기관: Omar H

•2021년 1월 1일

Great course! This is exactly how education should be! Give us the intuition to what we are doing, relate it to real world problems and when is this knowledge useful and then get the opportunity to code that knowledge in python instead of wasting time with just hand calculations! Brilliant!

교육 기관: Joshua G

•2021년 2월 24일

Fantastic course providing a broad understanding of linear algebra for machine learning. The responsive quizzes and formal assessments provide a challenge and regular feedback on performance. Highly recommend taking their course for anyone who wants to develop the maths that underpins ML.

교육 기관: Hermes J D R P

•2019년 6월 8일

A great course to learn the fundamentals of Linear Algebra for Machine Learning. The programming assignments in Python were the best part of the course because when I studied Algebra at my university I only did boring manual exercises. I recommend this course completely, you'll enjoy it.

교육 기관: 刘佳欣

•2019년 5월 23일

This is an incredibly great course for linear algebra. Thank you so much for the neat and elegant explanation! Highly recommend it if you focus more on calculation without knowing the meaning behind matrices and vectors in your past linear algebra journey. Thanks a lot dear professors!!

교육 기관: sujith

•2018년 9월 8일

This course has exceeded my expectations in some ways. I was just trying to get a refresher in basics of Linear Algebra. The intuitive understandings presented in the course were really helpful and gave me a better understanding of the concepts which I only learned mechanically before.

교육 기관: Jack C

•2018년 4월 6일

Great course, well presented videos and challenging but engaging content. Great high level view of linear algebra to give you a starting point for other courses. May be useful to have some machine learning knowledge before taking - Andrew Ng's course would serve as a good counterpoint.

교육 기관: Ben W

•2021년 11월 25일

This course provides an excellent overview of key linear algebra topics. The instructors do a great job building intuition about matrix transformations and eigenvalues/eigenvectors. Knowledge of python isn't required but will be helpful to do calculations and try out example problems.

교육 기관: Aleix L M

•2019년 11월 28일

After taking this course I can safely say that I did not understand Linear Algebra before. This course introduces basic concepts useful for machine learning and it gives a very intuitive view on abstract concepts that I had trouble understanding before. I would totally recommend it.

교육 기관: Satyajit S

•2018년 3월 18일

Great introductory course. Linear Algebra is quite often the most poorly taught/understood subject in college mathematics.This course has a done a great job in stressing on the core concepts without focusing on the computational details which happens in typical linear algebra courses

교육 기관: Curtis H

•2021년 7월 13일

It's been many years since I've reviewed these topics and this was as interesting and as painless as could have ever hoped. Production quality was top-notch and so was the teaching, felt engaged the entire time. I'm really looking forward to completing the rest of the specialization.

교육 기관: tharun n

•2021년 6월 8일

A great course with a lot of applications and visual explanations of basis, matrices etc. I really liked the approach used by the profs, explaining why we need to learn this rather than giving a bunch of equations and leaving us to figure out rest ( the way they teach in schools ).

교육 기관: Alexander Z

•2019년 8월 25일

Very much recommend this course for absolute beginners seeking to refresh/learn math required for machine learning.

Don't be afraid to start and focus on learning instead of going through the material.

Practice exercise you've done several times and return to your notes. Good luck!

교육 기관: Alok N

•2020년 4월 14일

Great course! Linear algebra is a very vast subject. This course helped me getting the idea of topics I need in machine learning algorithms. This course is very helpful in revisiting the linear algebra to those who have taken this subject in his/her college in very short time.

교육 기관: David N

•2021년 3월 30일

Excellent course. I was nervous starting the course, as I can find maths challenging, but I actually really enjoyed it and it has given me more confidence. In this course there is a focus on understanding what is being done and its applications, which is exactly what I wanted.

교육 기관: Wade W

•2019년 7월 12일

It's a worth-taking course. But you'd better have some linear algebra background. Like me, a student in China, we learn all things with out geometric insight, it will be very difficult for you to take the course through out.

All in all, worth-taking. Give me many fresh airs.

교육 기관: Dan L

•2019년 9월 29일

I actually studied Maths at undergrad and was using this as a catchup after many years - it wasn't taught nearly anywhere near as well as this. More lecturers should focus on the concepts first, and then the formulae to give context. A great course, highly recommended!

교육 기관: Anubhab G

•2018년 6월 6일

Well-paced, engaging and highly interesting course content. This course totally gives a new dimension to linear algebra. The fact that mathematical examples are implemented through programming exercises, really strengthens the concepts and makes it even more interesting.

교육 기관: Maged F Y A

•2018년 5월 1일

I would like to thank the instructors for their exceptional work. They are teaching mathematics with the aid of visualizations, which is not common within ordinary math classes. This way assists students to understand the physical interpretation of mathematical concepts.

교육 기관: Phuong A V

•2020년 7월 23일

It is quite hard course, especially coding.

the practice tests are very useful. Every test provides description which is very useful to review the lecture. Tests are challenging but if we make effort and invest time to think, read the instruction carefully, we can pass.

교육 기관: Henry N

•2020년 4월 5일

Lectures are well-paced (although I was familiar with basics of working with vectors and matrices from high school mathematics). The assignments and quizzes were pitched at the right difficulty, just hard enough to be a challenge but not so hard as to be disheartening.

교육 기관: Alireza S

•2021년 10월 12일

pretty nice course which contains linear algebra for machine learning. learned alot and had a lot of fun during the course and assignments. python assignments were great and challenging, final exam was so challenging. special thanks to instructors and Imperial College

교육 기관: Fabian d A G

•2021년 9월 7일

Really good course to deep dive into Linear Algebra for ML. The course is fast paced, but you get plenty of opportunities to practise. A Python programming component is present, in which you translate the mathematical working into a computer program. Tough, but good.

교육 기관: Pritam C

•2020년 9월 19일

Eigenvalue &Eigenvector, Matrix & Inverse Matrix, The Gram–Schmidt process, Page RanK.

I was weak in maths and my background was not that strong, But I learned here how to tackle with

wonderful lecture tutorials

I want to apply ML in my research in electric power system

교육 기관: Dariusz P G

•2019년 3월 10일

What an excellent lecturer.

I just wish that my mathematics teacher at school had had a tenth of the ability to impart knowledge.

This is a fantastic course and I will be doing the specialization later when I get some free time.

Thank you for a fantastic course.

Dariusz

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