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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: 8,603
Рецензии: 1,742

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

NS
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.

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.

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226–250 из 1,737 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: laszlo

21 апр. 2018 г.

Awesome course!!! The course is very helpful for those who are willing to build an intuition of linear algebra. The coding assignments are a bit easy for CS students, but allow you to understand what has been taught in the course.

автор: David S

23 июня 2019 г.

Excellent. Exactly what I needed. A linear algebra course in machine learning. Top notch presentations, materials, and explanations. A nice blend of concepts and detailed calculations especially in transformations and eigenvectors.

автор: Shwetha T R

14 сент. 2020 г.

I loved this course! Both Prof David Rye and Prof Sam Cooper were amazing and used brilliant techniques to ensure creative learning. I enjoyed the eigen vectors and values and pagerank algo module a little too much! Thanks a lot!

автор: PATHIRAJA M P H S

12 июля 2020 г.

The course contains very creative introductions to some of the linear algebra theories that I was already familiar with. Could get new intuitions and better, deeper understanding of those concepts. Really glad I took this course.

автор: Mohamed S

26 июня 2020 г.

I liked the course and huge number of exercises. Maybe my only problem is the academic form of the lectures that makes me lost sometimes and forces me to google for an Indian guy who can teach me the concept in a more easier way.

автор: Rahul S

28 окт. 2019 г.

This course is little challenging if one has not revised Linear Algebra before, but quite interesting and fun given the examples and utility only after learning the basics of linear algebra elsewhere and then attempting this one.

автор: Liam M

4 апр. 2018 г.

This is an excellent refresher of vectors and linear algebra, and although I did it years ago in college I still found some new insights from doing this course. Its all explained very well without being bogged down in formailty.

автор: Rohan A

9 июня 2020 г.

Great course guys! I have done a course on Linear Algebra in my university and watched the 3Blue1Brown series on Essence on Linear Algebra. This course was a good recap of the concepts and their applications in machine learning

автор: Ramy S R

27 сент. 2020 г.

Excellent course. Material is explained thoroughly through concise short videos with plenty of visualizations that make linear algebra intuitive. Assignments are chosen carefully and the curated python labs are very enjoyable.

автор: Prateek K S

28 мая 2018 г.

Nice course. This course is very good to build your fundamental knowledge for machine learning. This course gave me very clean and straight forward understand how mathematics play very important role in machine learning field.

автор: Himanshu G

13 июня 2020 г.

Thank you for designing such a wonderful course. I find difficulty in understanding the concepts related to eigenvalue and eigenvectors and Page Rank. Otherwise, the other concepts have been beautifully explained. Thank you!

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.