Self-study Linear Algebra textbook for ML and Stats

I am looking for a good linear/matrix algebra textbook, suitable for self-study, that covers topics relevant to statistics and machine learning. I have access to Gentle's "Matrix Algebra", but have found it to be too dry and more of a reference book for a practicioner who's already studied the subject before.

Some of the books I'm considering are:

Seber, "A Matrix Handbook for Statisticians"; Searle, "Matrix Algebra Useful for Statistics"; Harville, "Matrix Algebra from a Statistician's Perspective"; Gruber, "Matrix Algebra for Linear Models" (just came out)

and the more generally oriented:

Strang, "An Introduction to Linear Algebra"; Strang, "Linear Algebra and Its Applications"; Axler, "Linear Algebra Done Right"

The trouble is, all these text have excellent reviews on Amazon, but so did Gentle's text and it doesn't really suit my purposes.