Matrix Calculus (For Machine Learning and Beyond)
1–10 of 31 posts
Re: Matrix Calculus (For Machine Learning and Beyond)
#2> The class involved numerous example numerical computations using the Julia language, which you can install on your own computer following these instructions. The material for this class is also located on GitHub at https://github.com/mitmath/matrixcalc
Re: Matrix Calculus (For Machine Learning and Beyond)
#3The Matrix Cookbook [1] can be handy when learning this topic.
Re: Matrix Calculus (For Machine Learning and Beyond)
#4Those looking for a shorter primer could consult https://arxiv.org/abs/1802.01528
Re: Matrix Calculus (For Machine Learning and Beyond)
#5Great course. I highly recommended anyone interested in this topic to check it out on the MIT website, taught by the same authors. They are great lecturers.
Re: Matrix Calculus (For Machine Learning and Beyond)
#6What does calculus mean ?
Re: Matrix Calculus (For Machine Learning and Beyond)
#7What does calculus mean ?
Time to schedule with a dentist
Re: Matrix Calculus (For Machine Learning and Beyond)
#8If you want to get handy with matrix calculus, the real prerequisite is being comfortable with Taylor expansions and linear algebra.
In a graduate numerical optimization class I took over a decade ago, the professor spent 10 minutes on the first day deriving some matrix calculus identity by working out the expressions for partial derivatives using simple calculus rules and a lot of manual labor. Then, as the class was winding up, he joked and said "just kidding, don't do that... here's how we can do this with a Taylor expansion", and proceeded to derive the same identity in what felt like 30 seconds.
Also, don't forget the Jacobian and gradient aren't the same thing!
Re: Matrix Calculus (For Machine Learning and Beyond)
#9I have skimmed it, and it looks very good. It is actually not solely about matrix calculus, but shows a practical approach to differentiation in different vector spaces with many examples and intuitions.
Re: Matrix Calculus (For Machine Learning and Beyond)
#10If you want to get handy with matrix calculus, the real prerequisite is being comfortable with Taylor expansions and linear algebra. In a graduate numerical optimization class I took over a decade ago, the professor spent 10 minutes on the first day deriving some matrix calculus identity by working out the expressions for partial derivatives using simple calculus rules and a lot of manual labor. Then, as the class wa…
Can you give an example?