I am an a grad student looking for a tutor that can help me review linear algebra AND get a good working knowledge of data mining concepts. I've taken STATS 202 (Data Mining) and have a pretty good conceptual understanding of data mining, but the theoretical proofs behind it are more difficult for me, especially since I forgot much of my linear algebra I took in undergrad.
The topics I'm looking to understand are PCA and MDS (including mathematical proofs) and eiganvalue decomposition. There are a couple more newer methods like elastic net and sparse discriminate analysis I need help understanding as well (you probably haven't heard of them, but I can give you the papers that explain them).
I would prefer someone who has taken graduate level statistics courses, but exceptional undergraduates could work too. I am willing to provide competitive pay. Please email me to discuss this.
The topics I'm looking to understand are PCA and MDS (including mathematical proofs) and eiganvalue decomposition. There are a couple more newer methods like elastic net and sparse discriminate analysis I need help understanding as well (you probably haven't heard of them, but I can give you the papers that explain them).
I would prefer someone who has taken graduate level statistics courses, but exceptional undergraduates could work too. I am willing to provide competitive pay. Please email me to discuss this.