ADDITIONAL USEFUL LINKS FOR PRE-COURSE READING:
Probability: Events, random variables, expectations, joint, conditional and marginal distributions, and independence
http://srl.informatik.uni-freiburg.de/teachingdir/ws13/slides/03-ProbabilityRefresher.pdf
https://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/book.html
Statistics: Bayes' Rule, Priors, Posteriors, Maximum Likelihood Principle (MLE), Basic distributions such as Bernoulli, Binomial, Multinomial, Poisson, Gaussian.
https://www.sagepub.com/sites/default/files/upm-binaries/49259_ch_1.pdf
https://cbmm.mit.edu/sites/default/files/documents/probability_handout.pdf
http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf
Linear Algebra: Vector spaces, subspaces, matrix inversion, matrix multiplication, linear independence, rank, determinants, orthonormality, basis, solving systems of linear equations.
http://www.deeplearningbook.org/contents/linear_algebra.html
http://www.cs.columbia.edu/~djhsu/ML/mlnotes/linalg.pdf
https://www.math.ucdavis.edu/~linear/linear.pdf
https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/
Multivariate Calculus: Take derivatives and integrals of common functions, gradient, Jacobian, Hessian, compute maxima and minima of common functions.
http://tutorial.math.lamar.edu/pdf/Common_Derivatives_Integrals.pdf
https://www.tcd.ie/Economics/staff/paredesm/~EC2040/Lecture12.pdf
https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/
Mathematical maturity: Ability to communicate technical ideas clearly.
http://www.timhsu.net/courses/generic/write.pdf
http://www.timhsu.net/courses/generic/proof.pdf
http://www.timhsu.net/courses/generic/howto.pdf