Mathematics for Machine Learning: Linear Algebra(으)로 돌아가기

별점

10,706개의 평가

•

2,130개의 리뷰

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....

NS

2018년 12월 22일

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

2019년 9월 9일

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.

필터링 기준:

교육 기관: Jonathan F

•2018년 5월 20일

Excellent introduction. For me, as someone who had studied vectors and matrices at school, decades ago, it was wonderful to go back and re-learn this stuff in a different way. This course is much more focused on the meaning and usefulness of these things, rather than just learning how to do the maths. The first 3 minutes of the session on eigenvectors brilliantly showed in graphical form what they really are, something I'd never really grasped at school. Recommended.

교육 기관: Raymond I M J

•2020년 2월 2일

An excellent breakdown of linear algebra and the tools and processes that it takes to perform these operations. The lectures give you a good understanding of the concepts of vectors, scalars, dot product, matrices, and eigenvalues and vectors. I would highly recommend this course for anyone who is needing to understand how linear algebra can be conducted via computers, while still grasping the underlying concepts that make one proficient at linear algebra.

교육 기관: zachary k

•2020년 5월 10일

I had previously taken linear algebra, but this was a good refresher. The pace of this course is quite fast for 5 weeks, and the course does not dive into any proofs. It may be useful to get some outside supplements to get through the materials. I really enjoyed the way that the concepts were explained and presented such as eignvalues/vectors. They help provide some intuition instead of simply presenting the formula or grinding through proofs.

교육 기관: Nelson F A

•2019년 4월 25일

This is a great course! Be advised: It is very challenging and will kick your butt if you haven't seen much linear algebra before. The content in the course won't always be enough to solve all of the assignments. But look into the forums and use some other sources and you will succeed in this course. Overall I am glad I took it even if it will take a little longer until I can say that I master everything that was covered in the course.

교육 기관: Sébastien W

•2019년 6월 22일

The perfect dosage of the key elements in linear algebra to mastering the concepts of machine learning. The course leaves you with a clear intuition for vectors and matrices and how these objects can be manipulated, and most importantly why these objects are fantastic. I am an immunologist with a little background in machine learning and my last studies in mathematics taken 15 years ago, but this course has the perfect level I need.

교육 기관: Burouj A

•2019년 7월 6일

This course was like God-gifted.

I had just finished my 2nd sem at college(BTech) and we had Matrices in the syllabus so I knew how to calculate (just calculate -_-) eigenvalues, vectors and so on but I just saw them as numbers. At my college, we were not given such geometric insight and when I learned it through this course, MY GOD was I blown away.

I feel so lucky to have found this course! I learned A TON of stuff.

Thanks!!

교육 기관: FRANCK R S

•2018년 4월 15일

I took a great pleasure to study this linear algebra course, teachers are very talented since their way to explain mathematical concepts make it very easy to understand , in fact with this particular amazing approach I changed my perception about learning math and sciences in general. I do recommend this course if you look for a global overview of linear algebra for direct application in machine learning or computer sciences!

교육 기관: Luka

•2020년 5월 16일

I enjoy attending this course. I consider this course really good, mostly due to a lot of intuitive examples about particular subjects of study, explanations that were clear and enthusiastic professors. Finishing this course gave me motivation to learn more about machine learning and mathematics that it's based upon.

교육 기관: Karandeep

•2020년 10월 9일

This course is great for those who want to understand the geometric meaning of linear algebra. Really loved the course videos and quizzes. Just one suggestion - Coding assignments should be bit more challenging as this course is targeted around ML, maybe some small Kaggle like project at the end of course.

교육 기관: Siddhant J

•2020년 4월 13일

Excellent, crisp and to the point. Instructors made the concepts way to easy to understand. Enjoyed my time learning from them and ofcourse relevant material was provided.

교육 기관: Michael P

•2021년 6월 27일

I think Professor David Dye's Linear Algebra video is the best course. It's much more clear, intuitive, and focused in the machine learning domain. I like it so much!!!

교육 기관: David S

•2021년 1월 1일

A good value, well organized, with many exercises for practice. Effectively uses visuals, and contains the occasional very creative example.

Some caveats

a) this course is not for the absolute beginner. You'll need secondary / high school math, and basic familiarity with python

b) understanding linear algebra at this level is a second year full semester course at university. So if you want to understand the concepts - rather than just get the certificate - be prepared to use outside resources and invest considerably more time than advertised. Some linear algebra topics are skipped (cross product), and others are not well integrated into the course (Einstein summation)

c) while linear algebra is central to understanding machine learning, there are very few machine learning applications in this course.

And finally a small annoyance: I wish the instructors would get out of the way of the whiteboard at the end, so I could get a screen capture.

Overall, a worthwhile course.

D

교육 기관: khaled W S

•2019년 3월 25일

totally enjoyed it. requires a bit of side research as any online course would. some of the quizzes were not directly related to the video that preceded them as one would expect. However, a fun course and covers a lot of important basics for it's relatively short duration.

교육 기관: JUNXIANG Z

•2019년 5월 17일

This course reviews the essential concept of linear algebra in the context of machine learning. However, it would be much better if it provided more optional exercise and reading materials.

교육 기관: Ralph T

•2019년 5월 4일

decent course. It gives a good enough background to understand the mathematics necessities of many areas of data science. could be more thorough and dive deeper into some of the content.

교육 기관: Mark J T

•2019년 8월 2일

Good course because it shows how to understand geometrically, things that I had hitherto only understood computationally.

교육 기관: Philip A

•2019년 5월 16일

Excellent Instruction

교육 기관: Neel K

•2020년 5월 10일

For the most part, I enjoyed this course. Most of the math explained is fairly easy to understand. They cover the fundamentals of linear algebra, and provide plenty of assignments and practice exercises to test your knowledge. However, some of the video explanations are extremely confusing and feel rushed. For example, some videos in Week 4 and 5 like Reflecting in a plane using Gram-Schmidt and the PageRank algorithm were so hard to understand that I had to learn about them from elsewhere on the internet (I used MIT OCW a lot). This isn't very convenient, especially if you're paying for the course. Furthermore, I felt like more videos explaining the applications of linear algebra in machine learning could've been made, and the ones that were already made could've been made in more detail (for example, the term 'span' was never formally explained). Lastly, I would've loved it if there was another week dedicated solely to introduce the coding bit, because it's really difficult and takes a while if you have little or no prior experience in python. All in all though, I enjoyed this course, and I would recommend trying to complete both Linear Algebra and Multivariate Calculus in one month, because it's not worth paying more than that.

교육 기관: maytat l

•2019년 11월 20일

Challenging course. Much more difficult that I expected. It took me 7-9 hours a week. The overall course material itself was good building-blocks to further understand application of machine learning. However, explanation in some topics should have more detailed explanation and examples to further understand the concept. There were many times, I need to re-watch each video over and over again, paused it, and figured things out on my own. The programming assignments were the most challenging task. I just began to learn Python and found it very difficult because there were so many codes I haven't learnt before. I think for those who has not learnt Python at all may find really really difficult to pass the assignments.

교육 기관: Peter B H

•2019년 11월 26일

The content was good, but a couple of times what was said didn't gel with what was being drawn/written/done. Since I'm learning, this took me longer to double check when I misunderstood something whether it was the concept or a mistake in the delivery.

교육 기관: Pedro C O R

•2019년 8월 1일

The topics could be improved in the way they are presented. I always had to search for additional material.

However, the course is okay, it could be better, the forum is not that active, and some assignments are good.

교육 기관: kai k

•2019년 5월 5일

many of the activities are excellent, but videos hard to follow along to at times - play them at 0.75 speed if you can. Also, the faculty is not super responsive it seems on discussion boards creating some confusion

교육 기관: Girisha D D S

•2018년 8월 27일

Although the course content is good, I feel it could have been done better. I enjoyed the multivariate calculus course compared to this course.

교육 기관: Maximilian P

•2018년 12월 12일

Some exercises are completely incoherent to the preceding videos, which makes it very difficult to solve them. very frustrating

교육 기관: Dr. V N R

•2020년 12월 9일

Assignment makes frustration and not able to concentrate on teaching content

- Google 데이터 분석가
- Google 프로젝트 관리
- Google UX 디자인
- Google IT 지원
- IBM 데이터 과학
- IBM 데이터 분석가
- Excel & R을 사용한 IBM 데이터 분석
- IBM 사이버 보안 분석가
- IBM 데이터 엔지니어링
- IBM 풀스택 클라우드 개발자
- Facebook 소셜 미디어 마케팅
- Facebook 마케팅 분석
- Salesforce 영업 개발 담당자
- Salesforce 영업 운영
- Intuit 부기
- Google 클라우드 자격증: 클라우드 아키텍트 취득 준비
- Google 클라우드 자격증: 클라우드 데이터 엔지니어 취득 준비
- 경력 시작
- 수료증 취득 준비
- 경력 쌓기