Skip to main content

Someone wanted to learn this too, so Grasp built them a personal learning path.

You can keep exploring this one or create a path like this one shaped around you.

Maths for Machine Learning

12 Modules · 95 Lessons

Recommended resources

Module 2

Single-Variable Calculus Essentials

Module 3

Vectors, Matrices, and their Properties

Module 4

Vector Spaces and Linear Mappings

Module 5

Eigenvalues and Matrix Decompositions

Module 6

Multivariable Calculus and Gradients

Module 7

Foundations of Probability

Module 8

Probability Distributions and Expectations

Module 9

Multivariate Probability and Statistics

Module 10

Parameter Estimation Techniques

Module 11

Optimization for Machine Learning

Module 12

Mathematical Synthesis in Machine Learning