Reddit mentions of Linear Algebra Done Right (Undergraduate Texts in Mathematics)

There's like a million textbooks and online courses on the subject, and I can't really speak to which ones are good and which ones are not. I've had some success suggesting that people watch this lecture series, but it starts off assuming a fair amount of background. If you're just planning to have some fun noodling around I strongly recommend that you look up a tutorial that suits you on the Keras library for Python, which will let you get started building cat/dog classifiers very easily but which scales up to exploiting the full power of Tensorflow. If you're interested in getting a bit more serious I'd suggest getting comfortable with linear algebra (great book) and making sure you really understand backpropagation. It might sound elitist, but if you can't derive it from scratch on a whiteboard you don't actually understand it, and it will limit your ability to understand why many other techniques are useful.

From there you should have the grounding to understand basically all of the entry-level stuff in the field, from support vector machines to convolutional neural networks.

he's okay.

just don't come into class late.

the textbook for linear algebra wasn't great

some additional resources:

https://www.youtube.com/watch?v=kjBOesZCoqc&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

https://open.math.uwaterloo.ca/2?gid=395

http://joshua.smcvt.edu/linearalgebra/

https://www.amazon.ca/dp/3319307657

https://www.math.brown.edu/~treil/papers/LADW/LADW.html

https://www.amazon.ca/dp/0130084514/