Back to Mathematics for Machine Learning: Linear Algebra

4.7

3,716 ratings

•

670 reviews

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....

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.

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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By Prateek J

•Apr 30, 2018

Good course for refreshing your knowledge in Linear Algebra. Easy to understand material and instructor is great.

By Kohinoor G

•Apr 24, 2018

One of the best Linear Algebra [LA] courses for beginners/novices. It takes away the drudgery of algebra and formulae and tries to explain the "essence" of LA. This is by no means comprehensive LA course - but good enough for people who are fed up with "this is how to calculate the Eigen vector/determinant/<insert pet peeve>" mode of teaching LA.

By Xiao F

•Apr 20, 2018

very good course for high level aspect of linear algebra

By Vincent L

•Jun 09, 2018

I took this course as a review for my data science curriculum. Previously, I was having trouble recalling the details of matrix arithmetic which was making it hard for me to get a deeper understanding of machine learning. After doing this course, you should have no trouble following along. For those already familiar with the material, it should take about 1-2 weeks to complete if working at a leisurely pace.

By Julio V E

•May 21, 2018

Excellent course, with a great team of well-motivated instructors.

By Pavani R

•Apr 22, 2018

very well designed course. After a long search for perfect math intro to ML this was the perfect course i stumbled upon. Instructors are engaging and content is relevant.

By Charles E

•May 05, 2018

Great short intro to linear algebra. Excellent treatment of eigen problems.

By Jnaneswararao B

•Jun 09, 2018

changing the basis and reflecting plane helped me lot

By 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.

By Vinay P K

•Mar 10, 2018

Good Refresher.

By Ronny A

•Jun 11, 2018

Excellent Linear Algebra refresher. I love it that this course distills and covers the core concepts in a very time efficient manner! Also, I am happy with the emphasis on images and graphs to develop intuition. The programming exercises such as Reflecting Bear and Page Rank have been curated well.

By 郭立

•Jun 07, 2018

excellent!!!

By Maciej K

•May 15, 2018

great course, gives clear info on linear algebra.

By Dharma T N

•May 09, 2018

This is indeed one of the best math courses I have ever done in my life. This course changed the view I look at matrices and vectors. I have been 'transformed'.

The instructors were simply amazing. Totally loved every bit of the course. Amazing way to teach this math course, with proper motivation and intuition.

And for all the people writing negative reviews about no Machine Learning being taught in this course, it is clearly mentioned that this course teaches the math which is required for learning Machine Learning and not Machine Learning itself.

By Jitender S V

•Jun 30, 2018

This is the BEST course if anyone wants to learn linear algebra for machine learning. Lectures are clear and very understandable and quiz questions are great, too. Thank you for this great course.

By Cynthia M

•May 19, 2018

I enjoyed the presenter's. The course helps you see how linear algebra is connected to data science.

By Bomma L K

•Mar 31, 2018

very intuitive, must have of clear description of LA

By Marakhi D

•May 08, 2018

Great course.

By laszlo

•Apr 21, 2018

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.

By Xiaoyuan C

•May 21, 2018

Super interesting and impressive course

By Annamalai S

•Jul 03, 2018

Really great course!

By Joe E

•May 02, 2018

Great course with great instructors.

By Vitória C

•Jul 11, 2018

The content of the course is very relevant, and the instructors are really fun and helpful.My only suggestion is to upload revisions for each assessment, so we can understand what we are doing wrong.

By Bálint - H F

•Jun 06, 2018

Very very good !

By Timo K

•Mar 28, 2018

Pros:

Amazing explanations of the covered topics, extremely engaging teaching staff

Focusses on the right things

Good and enough practice problems

Great (albeit easy) programming problems

Cons:

Calculation of Eigenvectors could have been covered better in my opinion

A final handout for all the covered topics would be really nice

Overall a tremendous course if you want to brush up on linear algebra. To me LA was taught mostly doing rote calculations without motivating the concepts or explaining them geometrically. I had more than a handful of "oh, so that's how this actually works" moments. I feel like my intuitive understanding of linear algebra concepts has made a big improvement.

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