A student's guide to COMP9418 at UNSW: what the course covers (Bayesian networks, exact and approximate inference, HMMs, learning), the Darwiche textbook, the open-book exam format, and free notes for every topic.
Machine-Learning
Lab 2
The Chapter 2 lab is a tour of the language itself – vectors, matrices, indexing, plotting, and loading a data set. What follows is that tour, split into the sections the book uses.
Basic Commands
Vectors are built with c() (concatenate), and both <- and = assign. Arithmetic is element-wise, so operands must share a length – reassigning x to length 3 lets it line up with y:
Worked solutions to the exercises in Mathematics for Machine Learning by Deisenroth, Faisal, and Ong — linear algebra, analytic geometry, matrix decompositions, vector calculus, probability, and continuous optimization.