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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

4.7
5,020 個評分
926 條評論

課程概述

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....

熱門審閱

NS

Dec 23, 2018

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

Sep 10, 2019

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 - Mathematics for Machine Learning: Linear Algebra 的 250 個評論(共 920 個)

創建者 Edwin G P P

Sep 01, 2019

El curso desarrolla varias herramientas importantes para el manejo de vectores y matrices enfocadas en aplicaciones de Machine Learning. Es bastante intuitivo.

創建者 aman

Aug 18, 2018

This course is a must for all the people who wants to go deep into machine learning and data science as this covers the prerequisites of the courses available.

創建者 Rambabu Y

Jul 28, 2018

It is highly recommended. Very useful to those who are interested in AI and ML and looking for deep dive. Thanks very much coursera and imperial college London

創建者 V A R

Jun 15, 2019

Brilliant course, thought intuitively and had a significant impact on my perspective in viewing transformation and other operations related to linear algebra.

創建者 Zvinodashe M

Jul 26, 2018

Excellent course a little challenging but just the right pace and depth to get one back up to speed with linear algebra, looking to build from this foundation

創建者 Kyle W

Dec 06, 2018

Excellent course. It's very practical - focuses on building your intuition of core concepts and applying those concepts through simple programming exercises.

創建者 Anastasios P

Dec 22, 2019

Great course to get introductory knowledge and good foundation on linear algebra, especially Eigenvalues and Eigenvectors and some basic python programming.

創建者 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.

創建者 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).

創建者 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.

創建者 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, ...

創建者 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.

創建者 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.

創建者 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.

創建者 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!

創建者 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.

創建者 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

創建者 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.

創建者 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.

創建者 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.

創建者 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.

創建者 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!

創建者 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.

創建者 AVICHAL

Mar 27, 2020

This course teaches complex theories of Linear Algebra in a simple way. Coding Practice problems were very useful in implementing the learning.

創建者 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.