If you don’t care about accreditation and are patient, sit down with Axler’s Linear Algebra Done Right and Hoffman & Kunze’s Linear Algebra, in that order.
I would caution you against trying to learn linear algebra using a “take what you need” approach. A random walk approach to learning the material is faster than an accumulation approach, but it’s more brittle and prone to confusion. A lot of things which appear to be irrelevant or unnecessary for machine learning (computation or research) can be imperative for understanding or implementing much more complex concepts later on.
If you don’t care about accreditation and are patient, sit down with Axler’s Linear Algebra Done Right and Hoffman & Kunze’s Linear Algebra, in that order.
I would caution you against trying to learn linear algebra using a “take what you need” approach. A random walk approach to learning the material is faster than an accumulation approach, but it’s more brittle and prone to confusion. A lot of things which appear to be irrelevant or unnecessary for machine learning (computation or research) can be imperative for understanding or implementing much more complex concepts later on.