A short Coursera course from Imperial College London covering the linear algebra needed for machine learning, including vectors, matrices, and eigenvalues/eigenvectors. It is part of Coursera's Mathematics for Machine Learning certificate.

Commenters recommend it as a clear, intuitive starting point for vectors, matrices, and eigen calculations, with one calling it a good first step toward core ML theory.

On Reddit (8)

1. Strongly recommendsstarbucksresidentr/learnmachinelearning2019in “Bayesian Decision Theory - hyperplanes”▲ 1

   highly recommend the course mathematics for ml: linear algebra on coursera run by imperial.... even helped me calculate eigenvalues... and im pretty piss poor in math

2. Recommendsstarbucksresidentr/learnmachinelearning2021in “How much linear algebra is required to be able to follow core ML theory?”▲ 3

   Basically Linear Algebra to around Eigen level, Eigenvectors/values, that is from scratch perhaps 15-20 hours of self-study. Take a course such as Imperial/Coursera Linear Algebra for Machine Learning. Don't bother to go further than this unless you are going deep into Theory. I can barely just…

3. Recommendsstarbucksresidentr/learnmachinelearning2021in “Mathematics for Machine Learning”▲ 1

   Coursera has some great courses, including Imperial College Linear Algebra for Machine Learning, also a good book on Bayes is one of a few released by James V Stone (various focusing on R and Python/General etc.) cheap but really easy to read and get to grips with. He also has a great book on ML…

4. Recommendsstarbucksresidentr/learnmachinelearning2021in “Mathematics for Machine Learning”▲ 4

   I took this course and got the Certificate (the Linear Algebra one). The Linear Algebra course has zero calculus and requires only you be able to solve simple linear equations and some trig - that's about it. It does however move at a fairly fast pace so it will perhaps take some time to complete…

5. Recommendshephaestus29r/learnmachinelearning2020in “Resources for Ml prerequisites”▲ 12

   Regarding Linear Algebra, I would recommend a course on Coursera https://www.coursera.org/learn/linear-algebra-machine-learning. I had taken this one prior to getting started on my long Machine Learning voyage. The concepts related to vectors and matrices have been explained elaborately giving you…

6. Mentionsnewjeisonr/learnmachinelearning2023in “How to learn machine learning?”

   depends on how much you care about the underlying math. If that's not important for you, just follow some tutorials. If you do care look into the Coursera course on the mathematics of ai

7. Mentionsbitcoinfugazir/learnmachinelearning2018in “Fastest way to learn about partial derivatives given I know next to nothing about calculus.”

   Coursera math for ml multivariate calculus course. If you desire you can also do the linear algebra course which is part of the specialization. You should be able to do week 1 in a few hours (refresher of single variable) and week 2 introduces partial derivatives

8. Criticizesstarbucksresidentr/learnmachinelearning2019in “New to ML. Grabbed these at thrift store for $8. Good buy?”▲ 1

   I undertook the Coursera / Imperial Certificate in Mathematics for ML: Linear Algebra and this video series was recommended. I think whilst it gives a warm feeling, on is own it is way, way too basic to use as any basis to move forwards. I'd recommended the Coursera course + 3B1B together... make…

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