Some of the main topics needed in machine learning are related to single variable calculus, linear algebra, multivariable calculus, multivariable optimization, probability and statistics and analytic geometry.

- Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong: Mathematics for Machine Learning.
- Professor Philippe Rigollet - MIT : Mathematics of Machine Learning.

- Khan Academy: Linear algebra including videos.
- Professor Gilbert Strang - MIT: Mit Open Course: Linear Algebra including lecture notes, videos and past exams with solutions.
- David Cherney, Tom Denton, Rohit Thomas and Andrew Waldron - UCDAVIS: Linear algebra.

- Prof. David Jerison - MIT: Mit Open Course: Single Variable Calculus including videos, lecture notes and past exams with solutions.
- Prof. Denis Auroux - MIT: Mit Open Course: Multivariable Calculus including videos, lecture notes and past exams with solutions.

- Professor Joseph Blitzstein - Harvard : Statistics 110: Probability including videos and Notes
- Philip B. Stark - University of California, Berkeley : Statistics including interactive tools included in the materials to help students analyze real datasets.
- Jeremy Orloff , Jonathan Bloom - MIT : Introduction to Probability and Statistics

- Professor Yaser Abu-Mostafa - Caltech : Learning From Data