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学生对 DeepLearning.AI 提供的 Linear Algebra for Machine Learning and Data Science 的评价和反馈

4.6
2,266 个评分

课程概述

Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful. After completing this course, you will be able to: • Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc. • Apply common vector and matrix algebra operations like dot product, inverse, and determinants • Express certain types of matrix operations as linear transformations • Apply concepts of eigenvalues and eigenvectors to machine learning problems Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works.  We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you’ll use....

热门审阅

MS

Aug 26, 2024

While people focus on teaching how to solve problems basically, It is very good to see people speak about maths like science as a concept with good visualization!. Great work guys.

PA

May 27, 2023

Best Visual Explanation, I've got new thinking of the same things which I had learned in the Past. It great Course Thanks for making Such Amazing Content.

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451 - Linear Algebra for Machine Learning and Data Science 的 475 个评论(共 525 个)

创建者 Luiz F P

Jun 12, 2024

First week was not amazing, but the remaining were very good!

创建者 Dev K

Jul 24, 2023

Great theory and maths. Programming portion can be improved.

创建者 Ammar J

Dec 5, 2025

Very helpful and take you step by step into course material

创建者 Mini I

Jul 3, 2024

very good explanation and practical part also very useful

创建者 Kareem W

Oct 28, 2023

Some of the material could have been explained better.

创建者 Hemanth R K

Jun 2, 2023

programming concepts should be explained more better.

创建者 Anshuman T

Jan 10, 2025

It is a very informative course, Thank you so much.

创建者 Guru P S

Jan 10, 2024

Proper Base and path for learning linear algebra

创建者 sitsawek s

May 21, 2023

in week 4 not completely clear about context

创建者 Olivier D T

Apr 16, 2023

Very clear, greatly enjoyable! Thanks a lot!

创建者 Miguel S

Sep 7, 2025

more practical exercises should be provided

创建者 Evert J K

Nov 12, 2024

Good course and gives a good understanding!

创建者 David K

Aug 13, 2024

Really good explanation of topics like PCA

创建者 Jay V

Mar 16, 2025

Learnt very depth of Linear Algebra.

创建者 Aleksey C

Jul 28, 2023

More exercises would be beneficial.

创建者 InFluX

Jul 25, 2023

Last week is a little confused.

创建者 Aymen K

Aug 7, 2024

is too hard for me but i pass

创建者 Tadeeb

Aug 13, 2025

good informative

创建者 Xiang Z

Feb 6, 2024

it's so deffcult

创建者 Abdullah M

Feb 29, 2024

It is too basic

创建者 Ryan V

Oct 5, 2024

Very Helpful:)

创建者 Basil E

Nov 2, 2023

good

创建者 M. R R

Sep 25, 2023

good

创建者 Abhinav J

Sep 23, 2023

good

创建者 Hau T

Apr 1, 2023

First, I'm a non-native English speaker, the language barrier is really a tough challenge for me to learn this course. However, I think this course is created for international learners, so these problems should be solved: - Luis's teaching is good. But I found there are some missing information or formula needed to solve the exercise. I have to Google a lot, which mean the course is not covered well.

- Exercises are really confuse sometimes. And it's not only me, I checked and many student got confused problems on Community.

- I would love to have more illustration. Some visual effect to point out which part Luis is talking about in the presentation is also good to have. Once again English is not my primary language, and Math is a lot of numbers, symbols and a lot of terminologies. I'm pretty sure even native ones may get lost too.

- I wish there is a Discord server for students, because it's usually quicker to get response there. The community page's UI/UX and navigation is not good. - Put the Notation on top of 4 modules. Why putting it at the end? I wish I knew it earlier.