Many folks have asked me what are the prerequisites to starting ML. There are some must-have and good to have pre-requisites that should/can be done before starting ML Here's my list Must have Linear algebra: vector spaces, sup-spaces, linear transformation, spectral decomposition, SVD, eigenvalues and eigenvectors Probability: fundamentals of distribution, PMF, PDF, some continuous and discrete distributions like Gaussian distribution Calculus: high school calculus. Information theory: the idea of entropy and mutual information Good to have Linear Algebra: operator and linear products, theory of solutions Probability: stochastic processes, moments and generating functions, Markov process Calculus: optimization under constraint, jacobian and Hessian, lagrangians Information theory: channel theory, information bottleneck