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Mathematics for Machine Learning

Post Graduate Program in AI and ML

Explore Mathematics for Machine Learning as part of Post Graduate Program in AI and ML. Read the syllabus and available chapters online.

Academic programmePost Graduate Program in AI and ML

LevelPost Graduate

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Mathematics for Machine LearningSyllabus

Mathematical Foundations Logic And NotationChapter 1

Vectors Matrices And Linear SystemsChapter 2

Matrix Decompositions And Spectral MethodsChapter 3

Analytic Geometry Projections And High Dimensional SpacesChapter 4

Multivariable Calculus And Automatic DifferentiationChapter 5

Probability And Random VariablesChapter 6

Statistical Inference And EstimationChapter 7

Statistical Learning Theory And GeneralizationChapter 8

Mathematical Optimization For Machine LearningChapter 9

Numerical Methods And Computational StabilityChapter 10

Information Theory And Probabilistic LossesChapter 11

Similarity Kernels And Dimensionality ReductionChapter 12

Probabilistic Graphical Latent And Sequential ModelsChapter 13

Decision Theory Causal Reasoning And Business AnalyticsChapter 14

Robust Responsible And Emerging Mathematics For AiChapter 15