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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: 4,808
Рецензии: 876

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

PL

Aug 26, 2018

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.

CS

Apr 01, 2018

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.

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226–250 из 873 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Xiran L

Jul 30, 2019

This course is amazing. Week 5 quiz is tricky but all the others are fine. The course might take longer than expected to complete but it's totally worth it.

автор: Sujeet B

Jun 19, 2019

Very good; contents covered gives an intuition of what's happening beneath the Mathematics. The lectures are interactive (which keeps your brain working).

автор: GUO J

Nov 05, 2019

The programming assignments are very well-designed. They are easily to follow and give me confidence to use Python deal with complex mathematic problems.

автор: Serge H k

Nov 25, 2018

I love the stuff that I learned: the usefulness of eigenvalues and eigenvectors, coding pagerank algorithm, gram Schmidt to create orthonormal basis, ...

автор: Lee F

Sep 07, 2018

Enjoyed the course a lot! It stretched me at times, and I definitely got what I needed and know where to go to fill in any knowledge gaps in the future.

автор: SANDEEP K D

Nov 09, 2019

A new way of looking at eigen values and vectors, every engineer should do this course.

It will help developing strong fundamentals for machine learning.

автор: Wookjae M

May 03, 2019

It was a "neat" lecture for understanding the basic of linear algebra. Programming assignments and test were well designed. Thank you for the lecturers.

автор: Gabriela S

Nov 03, 2019

Great approach, teaching the intuition of mathematics, this is exactly what I was looking for! Thank you to the amazing instructors for the fun course!

автор: Rushil

Sep 03, 2018

Fantastic recap on linear algebra concepts.

The focus on intuitive understanding is a pleasure and far more engaging than more traditional approaches.

автор: Aman A

Oct 09, 2019

One of the most concise and yet complete courses on Linear algebra in the light of its practical application in the real world and machine learning

автор: Mohammad A M

Oct 22, 2019

This course gives you an in-depth understanding of Linear Algebra concepts that are momentous for Machine Learning, so DO NOT hesitate to take it.

автор: Hritik K S

Dec 08, 2018

I learned the best visualisation of linear algebra's concepts. Nothing is better that understanding the concepts and how the things are happening.

автор: Amod

Jun 11, 2018

Extremely Helpful.Every Machine Learning Aspirant should complete this course to get the basics right! Instructors and Course Content are perfect.

автор: yifei l

Dec 21, 2019

Great linear algebra part, compare to regular linear algebra class. This class focues more on intuitive and practice. I really enjoy this class.

автор: ChaoLin

Oct 25, 2018

only the homework is not so friendly to the people who do not use python often, and the other is so good, especially about the teachers, thanks!

автор: Nigel H

Apr 18, 2018

Very high production standards, well presented by enthusiastic staff and very manageable as the material is taught so well. Highly recommended.

автор: Brandi R

Jun 20, 2019

Wow, this course was hard. But very good, I learned so much about transforming vectors and matrices as well as some interesting Python coding.

автор: Oj S

Dec 13, 2019

A very useful course for Machine learning, you will never feel aloof if you are not with a Mathematics background while learning ML afterward.

автор: Asrorbek O

Jun 21, 2019

The course is very great. I have thoroughly enjoyed taking it. However, 5th module should be improved by teaching diagonalization more deeply.

автор: Robert P C J

Jul 01, 2018

This course was a really excellent refresher in linear algebra! Everything was presented clearly, and the lectures and homework were engaging.

автор: Brian A W

Dec 12, 2019

Very informative, even as I start my postgraduate studies, I have picked up on a few notions and perspectives I have never considered before.

автор: Nano D N

May 14, 2019

I'm only at the beginning of the course but the material is really worth it.

Great instructor. He makes himself very clear and easy to follow.

автор: Camilo J

Feb 18, 2019

Great class and wonderfull material. Focused on intuition and programming rather that minndlessly solving problems as a mechanical challenge.

автор: Yuen P H H

Apr 02, 2018

Website works really well and the course material is clear and concise where the lecturer describes the theory and its application very well.

автор: Nathan R

Jan 23, 2020

I needed a course to understand basic of linear algebra prior to starting masters course in discrete optimization. This course was perfect.