Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
I'm e-learning Linear Algebra right now to have a good math foundation for Machine Learning.I was a History and Sociology major in college - so I didn't take any math.If you are like me, and working off an initial base of high school math, I would recommend the following (all free):Linear Algebra Foundations to Frontiers (UT Austin)
Course: https://www.edx.org/course/linear-algebra-foundations-to-fro...
Comments:  This was a great starting place for me.  Good interactive HW exercises, very clear instruction and time-efficient.Linear Algebra (MIT OpenCourseware)
Course: https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra...
Comments:  This course is apparently the holy grail course for Intro Linear Algebra.  One of my colleagues, who did an MS in EE at MIT, said Gilbert Strang was the best teacher he had.  I started off with this but had to rewind to the UT class because I didn't have some of the fundamentals (e.g. how to calc a dot product).  I'm personally 15% through this, but enjoying it.Linear Algebra Review PDF (Stanford CS229)
Link:  http://cs229.stanford.edu/section/cs229-linalg.pdf
Comments:  This is the set of Linear Algebra review materials they go over at the beginning of Stanford's machine learning class (CS229).  This is my workback to know I'm tracking to the right set of knowledge, and thus far, the courses have done a great job of doing so.