Back to Mathematics for Machine Learning: Linear Algebra

stars

10,388 ratings

•

2,078 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....

PL

Aug 25, 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

Mar 31, 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.

Filter by:

By zachary k

•May 10, 2020

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.

By Nelson F A

•Apr 25, 2019

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.

By Sébastien W

•Jun 22, 2019

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.

By Burouj A

•Jul 6, 2019

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!!

By FRANCK R S

•Apr 15, 2018

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!

By Luka

•May 16, 2020

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.

By Karandeep

•Oct 9, 2020

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.

By Hussin E

•Aug 9, 2021

the instrutors were too good and their explination for the concepts was to the point and it made me realize things in linear algebra I didn't know before although I studied it in school of engineering

By Siddhant J

•Apr 13, 2020

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.

By Michael P

•Jun 27, 2021

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!!!

By David S

•Jan 1, 2021

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

By khaled W S

•Mar 25, 2019

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.

By JUNXIANG Z

•May 17, 2019

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.

By Ralph T

•May 4, 2019

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.

By Mark J T

•Aug 2, 2019

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

By Philip A

•May 16, 2019

Excellent Instruction

By Neel K

•May 10, 2020

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.

By maytat l

•Nov 20, 2019

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.

By Peter B H

•Nov 26, 2019

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.

By Pedro C O R

•Aug 1, 2019

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.

By kai k

•May 5, 2019

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

By Girisha D D S

•Aug 27, 2018

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

By Maximilian P

•Dec 12, 2018

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

By Dr. V N R

•Dec 9, 2020

Assignment makes frustration and not able to concentrate on teaching content

By Amit V

•Sep 8, 2020

1.) This is definitely not a course for beginners, especially if one does not know how to code OR if he/ she is weak in coding.

2.) As far as lectures are concerned, the faculty members/ lecturers are energetic. While some topics have been explained really well, many topics are either left without much explanation. There are some occasional mistakes on the part of faculty, which must've been edited and rectified. They have done good job in converting the lectures in to text. However, there were some mistakes in those texts too.

3.) There is no support in discussion forums from the lecturers of this course. I have seen many questions remain unanswered for many months. This is a very big drawback.

4.) There is a huge gap between what is being taught in videos and what is being asked in assignments. We can understand this by the following corollary: In the video tutorial one teacher is showing that 1 + 2 = 3. In the assignment, students are being asked to find the roots of a quadratic equation.

5.) Some questions and even their answers too technical to be understood by many students. The attempt to explain after the completion of assignment is also too technical. There should be an attempt to dive deeper to help weaker students. If time is the constraint, then make another basic course and let that be a prerequisite of this course. But please, do not mention in the introduction of this course that there is no prerequisite.

- Google Data Analyst
- Google Project Management
- Google UX Design
- Google IT Support
- IBM Data Science
- IBM Data Analyst
- IBM Data Analytics with Excel and R
- IBM Cybersecurity Analyst
- IBM Data Engineering
- IBM Full Stack Cloud Developer
- Facebook Social Media Marketing
- Facebook Marketing Analytics
- Salesforce Sales Development Representative
- Salesforce Sales Operations
- Intuit Bookkeeping
- Preparing for Google Cloud Certification: Cloud Architect
- Preparing for Google Cloud Certification: Cloud Data Engineer
- Launch your career
- Prepare for a certification
- Advance your career

- Skills for Data Science Teams
- Data Driven Decision Making
- Software Engineering Skills
- Soft Skills for Engineering Teams
- Management Skills
- Marketing Skills
- Skills for Sales Teams
- Product Manager Skills
- Skills for Finance
- Popular Data Science Courses in the UK
- Beliebte Technologiekurse in Deutschland
- Popular Cybersecurity Certifications
- Popular IT Certifications
- Popular SQL Certifications
- Marketing Manager Career Guide
- Project Manager Career Guide
- Python Programming Skills
- Web Developer Career Guide
- Data Analyst Skills
- Skills for UX Designers

- MasterTrack® Certificates
- Professional Certificates
- University Certificates
- MBA & Business Degrees
- Data Science Degrees
- Computer Science Degrees
- Data Analytics Degrees
- Public Health Degrees
- Social Sciences Degrees
- Management Degrees
- Degrees from Top European Universities
- Master's Degrees
- Bachelor's Degrees
- Degrees with a Performance Pathway
- Bsc Courses
- What is a Bachelor's Degree?
- How Long Does a Master's Degree Take?
- Is an Online MBA Worth It?
- 7 Ways to Pay for Graduate School
- See all certificates