Linear Algebra Done Right and ESL

[MikeLawrence]

I'm in a 'linear mathematics II' course right now and I think it covers all of Linear Algebra Done Right. Dang near most of it, at the very least.

For those who know, what are the odds I can understand all the math behind the concepts in Elements of Statistical Learning after this course?
Also, what is your thought on this course more generally. It appears to give enough of a foundation to get the plumbing behind many applied ideas, and therefore is very useful, but I'm not on the other side yet so I'm not sure what it's use will be in practice.

 

[Daniel Duffy]

What's "ESL"?

 

[MikeLawrence]

What's "ESL"?

edited. ESL -> Elements of Statistical Learning

 

[Daniel Duffy]

edited. ESL -> Elements of Statistical Learning

I see.
Some numerical linear algebra and optimisation preparation is very useful.

 

[MikeLawrence]

I see.
Some numerical linear algebra and optimisation preparation is very useful.

I'll take a course in NLA either this spring or next fall.
My uni doesn't seem to have great optimization courses. I asked a prof about one and he said it was more for maths teachers (high school level) than hard mathematicians.

Just wondering if it the course covers the basis for these types of models.

 

[Daniel Duffy]

I asked a prof about one and he said it was more for maths teachers (high school level) than hard mathematicians.
Your prof is not even wrong.
Scary.

 

[MikeLawrence]

I asked a prof about one and he said it was more for maths teachers (high school level) than hard mathematicians.
Your prof is not even wrong.
Scary.

Did you go and find the courses at my uni?
I assume you aren't commenting on optimization in general, or you wouldn't have recommend it to me.

4000 Level

MTH 4312 - Cryptology Prerequisite(s): MTH 2311, and either MTH 3312 or CSI 2350; or consent of instructor. Introduction to cryptology, the study of select codes and ciphers. Included is a historical content, a survey of modern crypto systems, and an exposition of the rule of mathematical topics...

math.artsandsciences.baylor.edu

The optimization course was a 3000 level, but there are some others (e.g.: the three 'numerical' ones, 1x3000 2x4000) that I'm looking forward to taking.

 

[Quasar Chunawala]

I'm in a 'linear mathematics II' course right now and I think it covers all of Linear Algebra Done Right. Dang near most of it, at the very least.

For those who know, what are the odds I can understand all the math behind the concepts in Elements of Statistical Learning after this course?
Also, what is your thought on this course more generally. It appears to give enough of a foundation to get the plumbing behind many applied ideas, and therefore is very useful, but I'm not on the other side yet so I'm not sure what it's use will be in practice.

From this post on Stats SE, LADR should kinda be good enough. My plan is to work through the baby book first - ISLR.

What math background do I need to read ESL effectively?