MyPhatshala

Mathematics for Machine Learning

The linear algebra, calculus and probability behind every ML model, explained visually.

Intermediate3 modules10 lessonsFree · no sign-up
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Syllabus

01 Linear AlgebraVectors and matrices. 4 lessons
  1. 1.1Vectors and vector operationsComing soon
  2. 1.2Matrices and matrix multiplicationComing soon
  3. 1.3Eigenvalues and eigenvectorsComing soon
  4. 1.4Matrix decompositionComing soon
02 CalculusHow models learn. 3 lessons
  1. 2.1Derivatives and gradientsComing soon
  2. 2.2Chain ruleComing soon
  3. 2.3Gradient descent explained visuallyComing soon
03 Probability for MLUncertainty in models. 3 lessons
  1. 3.1Probability distributions for MLComing soon
  2. 3.2Maximum likelihood estimationComing soon
  3. 3.3Information theory: entropyComing soon