I have heard about uses of Algebraic Geometry in Statistics and Machine Learning. I wanted to try to learn a bit about this topics. I don't know nearly anything about Algebraic Geometry, but I have background in math, and I know about basic group theory, rings fields and some commutative algebra. My questions are:
What are the Algebriac Geometric concepts I should learn that are connected to applications in Stats/ML (I suppose only a portion of what is usually taught in Algebraic Geometric courses and books is useful).
Can you recommend some books / introductory papers for someone with my background? I don't mean standard textbooks for AG but something that focuses on concepts used in applications.