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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

4.7
звезд
Оценки: 9,063
Рецензии: 1,835

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

CS
31 мар. 2018 г.

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

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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251–275 из 1,829 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Neelam J U

14 июля 2020 г.

I really enjoyed the application of the abstract mathematical concept to real-world problems. This shift from conventional teaching of the subject makes one realise why math is at the core of all technological developments.

автор: Liu Z

6 мая 2019 г.

As for Chinese students, this course clearly explain the vectors, vector multiplication in a graph way, which for me is very useful, instead of in many Chinese university, which just state formula of calculating the vector.

автор: Jurij N

18 июня 2018 г.

I was very satisfied with the course. I'm really grateful for the effort they put into the programming exercises, so I finally began to put the theoretical knowledge into code. From now on I am able to experiment by myself.

автор: Fabricio O

22 мая 2019 г.

Great pace and content very nicely curated. Loved it and will carry on with the specialisation. I am a professor myself and I am also learning a lot about good practices when it comes to teaching. Could not recommend more!

автор: Aldrich W

17 авг. 2020 г.

Love this course! Prof. David Dye is exceptionally great at explaining these concepts and the British accent also promotes my learning substantially. I'll definitely take the second course in the specialization very soon.

автор: Christopher R

13 апр. 2020 г.

Excellent intuitive course in linear algebra. I had no idea how much I missed during my undergraduate studies. I think I went through this twice and might go through it once more. I would love another course by these two!

автор: Nacir

22 июня 2019 г.

Great course. The instructor is really great (and neat), communicates the ideas really well and if Imperial College London is ranked that high worldwide, it's definitely because they hire professors this good. Thank you.

автор: Vashista V

15 мая 2020 г.

I can now look at Linear Algebra in a completely fresh perspective from an application stand point. The course was neatly mapped out and I really benefited from the excellent content provided by Imperial College London.

автор: Christophe L

12 апр. 2020 г.

Wonderful Diploma, amazing teachers.

Even a guy like me, a medical doctor socialized in Emergency Medicine, enjoyed a lot this course;

I can't wait to attend to Multivariate Calculus.

Thank you much for your amazing work

автор: Huang X

12 мая 2018 г.

This course helps me a lot. I don't need to calculate the matrix by hand. I just need to get the concept of what is the matrix doing and use computer to calculate it. This is the most import thing I got in this course.

автор: Lee T C

27 нояб. 2020 г.

Very intuitive and visual explanation of Linear Algebra compared to traditional math courses. This course focuses on the intuition and understanding of the fundamental concepts, rather than tedious rote calculations.

автор: Katyaini R C

12 окт. 2020 г.

I liked every part of this course. Yes, I'll need to practice to make the concepts sit better in my head... perhaps re-visit some of my 11th/12th grade textbooks as well. But it was a better starting point than most.

автор: Vinitha M R

27 сент. 2020 г.

Thank you all instructors for the efforts undertaken to develop such highly informative lectures with amazing graphics. It was really enlightening to visualize the various concepts we had studied during our academics

автор: Naveen D

7 июня 2020 г.

Awesome course for linear algebra basics. I was able to visualize the subject and see how the concepts can be applied to real life applications. The videos were short, interesting, and informative. Great instructors.

автор: Harshit L

7 апр. 2020 г.

the basic concepts give you the right intuition on how things work in vectors and matrices.

I strongly recommend this course to the beginners in this field. especially the week4 and week 5 concepts are really helpful.

автор: Aero M

11 мая 2019 г.

Very good course for building your Linear Algebra foundation. If you are starting with Machine Learning then you should surely go through this course to build your intuition about what is happening behind the scenes.

автор: Salem A

14 июня 2020 г.

A simple background on linear algebra is useful to complete the course. It is not necessary, however, because the instructors are going to teach you everything you need in a clear and concise manner which was great.

автор: Sanjay G

7 мар. 2020 г.

If you are thinking/looking to do your career in machine learning or want to brush up your linear algebra concept and how this is used in Machine learning, then this course must consider or added to the to-do list.

автор: Linc T J J

29 нояб. 2019 г.

i really enjoyed the short and concise lessons and the notebook exercises to summarise and put to practice all the learning after the end of each week. Content is easy to understand and follow。 Thank you Imperial!!

автор: Saurav K

4 янв. 2019 г.

This is an amazing course. With right blend of assignments and quizzes . The lectures are very clear and nice examples have been used to simplify the content to an extent that any one can easily grasp the concepts.

автор: JISHNU B

7 дек. 2018 г.

This is a very good course - less of symbols and more of intuition,which is more important in applications. Profs are excellent communicators - even if you zero knowledge of the subject - you will get 100% of it...

автор: Md. S S

27 июля 2020 г.

Some of assignment problems were really challenging: especially in the Eigenvalue problems, in 5 th module. If anyone listen every single word of the instructor, he will definitely overcome. Very concise lectures.

автор: Sumedh K R

19 апр. 2020 г.

The course provides focuses on developing intuition to understand the math required to solve problems with only a fair amount of hand calculations. Looking forward to completing the courses in this specialization!

автор: 高宇

20 июня 2019 г.

This course is designed at a good structure and show me many intuitives on linear algebra. It does not need heavy hand calculation, instead, it brings me into the underlying zen and to a fast track of application.

автор: Diego C

20 янв. 2021 г.

The professors have done a terrific job at making linear algebra understandable -at an intuitive level-, applicable, and enjoyable. I'm confident this class will help me dive deeper into machine learning topics.