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Вернуться к Mathematics for Machine Learning: Linear Algebra

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

Оценки: 8,619
Рецензии: 1,747

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

22 дек. 2018 г.

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.

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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201–225 из 1,742 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Volodymyr C

27 янв. 2019 г.

Clearly explained and key equations are derived with good step sizes. Quizzes and assignments are challenging (which is good!) and have high expectations for learners (which is really good for my motivation). Overall, I am really enjoying this course.

автор: Agamjyot S C

3 июня 2020 г.

A really nice course, I had already done a Linear Algebra module in the university. But that was mostly mugging up and not knowing what this is used for. This course's geometric interpretation of all topics, helped me a lot and give a lot of insight.

автор: Nuthakamol

25 мар. 2020 г.

The presentation an way of teaching is excellence; however, the course should add more reference or additional source or materials for more in dept detail for the person who feel that the simplified explanation in the course are still not sufficient.

автор: Jonathan M

10 апр. 2020 г.

Extremely helpful. I haven't taken a linear algebra class in almost 5 years and by going through these videos it helped me regain an intuition towards the subject. The videos do a good job of tying the material back to machine learning as a whole.

автор: Cyprien P

3 июля 2020 г.

Great maths refresher content, with very useful 2D geometrics examples helping to build the intuition rather than just explaining the maths. I feel like I can understand this part of linear algebra now, and I know what to search for when I won't.

автор: Astankov D A

16 мар. 2020 г.

Great explanation of all the important things, with topical examples and practical tasks. Still, it seemed to me that the course was growing more and more complex exponentially by the end of it, so it was really hard to catch up starting week 4.

автор: Thomas F

18 апр. 2018 г.

Highly valuable introduction to linear algebra. Maybe the programming assignments are far too easy, while some of the quizzes definitely are hard. And the best part of the course was to introduce with it's videos on youtube.

автор: Randy S

12 мая 2020 г.

A good mix of theory in videos, simpler practice problems to reinforce the learnings, and scalable applications in Python. Very much enjoyed the course and feel like I've learned a lot about linear algebra and the applications in data science.

автор: Ryan M

10 апр. 2020 г.

I very much enjoyed the content of this class. The professor for the first 4 weeks was great! The professor for the 5th week seemed to move at a slightly faster pace with less in-depth instruction. His visual aids were pretty groovy though.

автор: ALEENA T

13 сент. 2020 г.

Excellent course for anyone who wants to know the nuances of Linear Algebra and its applications.The applications are not just mentioned,but one gets hands-on experience applying the concepts they learned,in code.Hats Off to the entire team!

автор: Shivam K

26 мая 2020 г.

The course is really helpful to those seeking clarity on the concepts. Week 4 and 5 really will really demand your attention. Loved every single bit of this course.

Would be glad if course would have included more visualisation to play with.

автор: CHIOU Y C

2 янв. 2020 г.

This is a good linear algebra course intro. May not be the one for who is looking for mathematical rigorous but it's enough for machine learning. Linear Algebra is important but not all topics and this course highlights the needed materials.

автор: Jaromir S

30 сент. 2019 г.

I needed a quick refresh of my prior knowledge of linear algebra for my MSc course and I wasnt disappointed. I also appreciated the complementary python exercises and the effort to put the material into a context of a real world application.

автор: Someindra K S

3 янв. 2019 г.

I got a lot of intuition about some fundamental aspects of linear algebra. Rest of courses on maths was very rigorous in terms of methods. This was more inclined towards applications in machine learning. I enjoyed the entire learning process

автор: Stefan B

8 апр. 2018 г.

It was fun to work through the course. Sometimes it was challenging as it has to be. Now I have a much better understanding of the topic. Especially appreciated is the approach of the instructors to build intuition: it worked for me, thanks!

автор: Danilo d C P

19 июля 2019 г.

I really enjoyed taking this course. I could review and learn for the first time some important topics for machine learning, in special the eigenvalues and eigenvectors classes. I'd like to thank the course's professors and collaborators.

автор: Omar R G

17 мар. 2019 г.

An excellent course on the fundamentals of linear algebra. It was great revisiting all this topics. I would also say that some knowledge on linear algebra would be useful for taking this course given the fact that the lectures are quick.

автор: Felipe C

29 нояб. 2020 г.

Very good course. I liked it a lot. Some abstract thinking required. The last week is a bit less well explained but OK nonetheless.

In my experience, the estimated times for completing the work are a bit optimistic, it took me more time.

автор: dhiraj b

21 апр. 2020 г.

Offered the much needed perspective of linear algebra to develop actual understanding, than just solving problems without understanding why and how actual computation works. I would like to thank the professors for such a great course.

автор: Duraivelu K

11 апр. 2020 г.

This course not only provided me the fundamental knowledge of Mathematics required to learn my next interested course of Machine Learning, but also helped me to kill the lockdown period due to covid-19 pandemic in a useful way at home.

автор: AKSHAT M

19 июля 2020 г.

Excellent course. Outstanding methodology. Great fun and intuition based leaning, kudos to David Dye, Sam Cooper and the ICL team. Thank you very much for bringing forward this course. Looking forward for many more courses from ICL :D

автор: Greg E

15 июля 2019 г.

I thoroughly enjoyed this course. After using matrices and vectors for decades in my work, I have finally gained some intuition about what the dot-product operation, determinant and eigen-vectors actually represent. Thank you so much.

автор: Jafed E G

6 июля 2019 г.

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

автор: Mark A C

22 нояб. 2020 г.

This course has provided me a better understanding of linear algebra concepts specifically on how eigenvalues, eigenvectors, matrices, and vectors can actually be observed or used in engineering (or even in day to day) applications.

автор: Vijayakumar

20 мая 2020 г.

It was a very good learning and I enjoyed a lot. Hoping to take the advanced level courses in Machine learning and related areas. Thank you very much Professors David dye, Samuel J Cooper and A Freddie Page. Hoping to see you again.