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學生對 伦敦帝国学院 提供的 Mathematics for Machine Learning: Linear Algebra 的評價和反饋

10,411 個評分
2,083 條評論


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....



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.


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


101 - Mathematics for Machine Learning: Linear Algebra 的 125 個評論(共 2,092 個)

創建者 Cristiano M F


Fantastic course. Much like what the reviews I read had anticipated. It is rigorous, the professors are competent and empathetic, and I feel they combined the right amount of theory with lots of practice (including on programming which was a first for me). Finally, they also made it clear that this is not a college-level course on linear algebra but instead a course on linear algebra that is specifically applicable to machine learning (as its title suggests) which is exactly what I was looking for. Thank you, Imperial College London!

創建者 Aditya P


I found this course excellent. For quite a long time, I have been struggling to understand what Eigenvectors and values mean and why do we bother to focus so much on Orthonormality. This course dealt with these concepts in a simple and lucid manner. It built the necessary math and intuition, which I liked the most. Also, this course really explained well why Matrices and its knowledge is important as it is useful in so many applciations. I am happy with the course and expect the same utility from the next course in the specialization

創建者 Battal U


Course is not boring from start to the end and course teacher are really good at speaking and teaching. They have great passion and they're fun. I like them a lot. I hadn't hard time to learn and make progress. Course is also very informative and made me passionate about expand my informations about the Machine Learning and other ares connected with Machine Learning like Data Science. Again I am thankful to everyone who made this course accessible to me and people who passionate to learn about Machine Learning core concepts!

創建者 Soumyadeep S


Both the professors right from the very beginning were not only very knowledgable but the way they delivered the lectures, it was really great. From the transformations to the rotations and shears, to the concepts of eigen values and page rank, this course is just so satisfactory for those who love mathematics . I learned a lot of things from this course, I started looking at vectors a lot differently. I would like to thank both the professors from the bottom of my heart for delivering such beautiful concepts.

創建者 Mikhail D


I see why some people are unhappy with this course (may be difficult to follow if you haven't seen Linear Algebra before / assignments are sometimes confusing), but I personally loved it. I took this course as a refresher for the main Linear Algebra concepts I last studied almost 10 years ago and the lecturers did a great job presenting the material in a very visual, intuitive, and over high-level way, making sure that you really get a feel of the main concepts instead of being buried in notation and formulas.

創建者 Pieter t H


This 5-week course, which can be completed in the evenings of one week, quickly give me intuition about matrices/linear algebra and their use in machine learning. Also, it's a step toward understanding PCA/ dimension reduction. The teachers are really good in explaining the difficult material, and there are enough short tests to practice. I recommend the course to all data scientists who are already able to pick a prediction algorithm with high accuracy, but want to understand the math behind it better.

創建者 jie


This course is a great introduction course to linear algebra. I am a quantitative finance guy and, to be honest, already forgot almost 90% of linear algebra I learned in college. It is always a little painful for me to code matrix multiplication during my work. I found this course before I went to amazon to buy a text book. This course saved me so much time and I really learned what I need to learn. Thank you so much.

The only con of this course is that: the python coding assignment is too easy.

創建者 Ameya P


Course would be easy if you have any background with linear algebra, but concepts through the scope of geometric application, which is fresh give new perspective to whole linear algebra than how its taught in class or Uni. Amazing instructors ! and great way to visualize things ! Please note This course is not suited for beginners and people looking for an introductory lecture to Linear Algebra! please have some introductory knowledge before you start off with this course . Thanks !

創建者 Bhargav R


It's SPLENDID!!! The courses covers all the relevant topics in very intuitive way, and gives a deep and concrete understanding of the underlying Linear Algebra topics !!!!

The assignments are designed in a way that it tests the skills in great way alongside giving opportunities to explore the dynamics and have fun !!!

It also teaches on programming skills by it's programming assignments and thus develops the overall skills needed to boost start any ML topic/ course !!!!!

創建者 Emil Y


Excellent course to get you to refresh or provide you with solid foundations of linear algebra, provided you supplement the course content with additional reading where you are either a bit "rusty" or completely new to a particular topic. I also find the quizzes and assignments particularly helpful in cementing your understanding of the material. Overall, I had a great experience and will strongly recommend this course to anyone on the quest to become a data scientist.

創建者 Xin Y


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!

創建者 Maximiliano B


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.

創建者 Orlando F


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.

創建者 Natasha M


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

創建者 Mohammad M U


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.

創建者 Prateek A


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

創建者 Harsh D


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.

創建者 ChristopherKing


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.

創建者 Karan M


T​his course takes you through a beautiful journey that keeps you interested throughout. The professors have an engaging manner of teaching, keeping your appetetie healthy, and peppering the meaty concepts with good examples time and again for clarity.

W​ould definitely recommend this course to anyone who wants to develop enough understanding of Linear Algebra to do well with their understanding of Machine Learning.

創建者 Shhruti


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.

創建者 Ashish S


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.

創建者 Ritesh S


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.

創建者 Raja K


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!

創建者 Vincent L


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.